Working recursion! and also handling multiple array shapes, and properly handling unnamed classes

nwb_linkml/adapters/adapter.py

@@ -46,6 +46,26 @@ class BuildResult:
         self.types.extend(other.types)
         return self
 
+    def __repr__(self):
+        out_str = "\nBuild Result:\n"
+        out_str += '-'*len(out_str)
+
+        for label, alist in (
+                ('Schemas', self.schemas),
+                ('Classes', self.classes),
+                ('Slots', self.slots),
+                ('Types', self.types)):
+            if len(alist) == 0:
+                continue
+
+            name_str = "\n\n" + label + ':'
+            name_str += "\n" + '-'*len(name_str) + '\n'
+            name_list = sorted([i.name for i in alist])
+            item_str = '\n '.join(name_list)
+            out_str += name_str + item_str
+
+        return out_str
+
 T = TypeVar
 Ts = TypeVarTuple('Ts')
 
@@ -59,7 +79,14 @@ class Adapter(BaseModel):
     def walk(self, input: BaseModel | list | dict):
         yield input
         if isinstance(input, BaseModel):
-            for key in input.__fields__.keys():
+
+            for key in input.model_fields.keys():
+                # Special case where SchemaAdapter Imports are themselves
+                # SchemaAdapters that should be located under the same
+                # NamespacesAdapter when it's important to query across SchemaAdapters,
+                # so skip to avoid combinatoric walking
+                if key == 'imports' and type(input).__name__ == "SchemaAdapter":
+                    continue
                 val = getattr(input, key)
                 yield (key, val)
                 if isinstance(val, (BaseModel, dict, list)):

nwb_linkml/adapters/classes.py

@@ -51,25 +51,28 @@ class ClassAdapter(Adapter):
 
         # Build this class
         #name = self._get_full_name()
+        kwargs = {}
         if self.parent is not None:
-            name = self._get_full_name()
+            kwargs['name'] = self._get_full_name()
         else:
-            name = self._get_attr_name()
+            kwargs['name'] = self._get_attr_name()
+            kwargs['tree_root'] = True
 
-        # Get vanilla top-level attributes
-        attrs = self.build_attrs(self.cls)
+        # Attributes
         name_slot = self.build_name_slot()
-        attrs.append(name_slot)
+        kwargs['attributes'] = [name_slot]
+        # Get vanilla top-level attributes
+        kwargs['attributes'].extend(self.build_attrs(self.cls))
+
         if extra_attrs is not None:
             if isinstance(extra_attrs, SlotDefinition):
                 extra_attrs = [extra_attrs]
-            attrs.extend(extra_attrs)
+            kwargs['attributes'].extend(extra_attrs)
+        kwargs['description'] = self.cls.doc
+        kwargs['is_a'] = self.cls.neurodata_type_inc
 
         cls = ClassDefinition(
-            name = name,
-            is_a = self.cls.neurodata_type_inc,
-            description=self.cls.doc,
-            attributes=attrs,
+            **kwargs
         )
 
         slots = []

nwb_linkml/adapters/dataset.py

@@ -23,8 +23,12 @@ class DatasetAdapter(ClassAdapter):
 
         res = self.handle_arraylike(res, self.cls, self._get_full_name())
         res = self.handle_1d_vector(res)
+        res = self.handle_listlike(res)
         res = self.handle_scalar(res)
 
+        if len(self._handlers) > 1:
+            raise RuntimeError(f"Only one handler should have been triggered, instead triggered {self._handlers}")
+
         return res
 
     def handle_scalar(self, res:BuildResult) -> BuildResult:
@@ -70,6 +74,47 @@ class DatasetAdapter(ClassAdapter):
 
         return res
 
+    def handle_listlike(self, res:BuildResult) -> BuildResult:
+        """
+        Handle cases where the dataset is just a list of a specific type.
+
+        Examples:
+
+              datasets:
+              - name: file_create_date
+                dtype: isodatetime
+                dims:
+                - num_modifications
+                shape:
+                - null
+
+        """
+        if self.cls.name and ((
+                # single-layer list
+                not any([isinstance(dim, list) for dim in self.cls.dims]) and
+                len(self.cls.dims) == 1
+            ) or (
+                # nested list
+                all([isinstance(dim, list) for dim in self.cls.dims]) and
+                len(self.cls.dims) == 1 and
+                len(self.cls.dims[0]) == 1
+            )):
+            res = BuildResult(
+                slots = [
+                    SlotDefinition(
+                        name = self.cls.name,
+                        multivalued=True,
+                        range=self.handle_dtype(self.cls.dtype),
+                        description=self.cls.doc,
+                        required=False if self.cls.quantity in ('*', '?') else True
+                    )
+                ]
+            )
+            return res
+        else:
+            return res
+
+
     def handle_arraylike(self, res: BuildResult, dataset: Dataset, name: Optional[str] = None) -> BuildResult:
         """
         Handling the
@@ -150,6 +195,9 @@ class DatasetAdapter(ClassAdapter):
             # if a dim is present in all possible combinations of dims, make it required
             if all([dims in inner_dim for inner_dim in dataset.dims]):
                 required = True
+            # or if there is just a single list of possible dimensions
+            elif not any([isinstance(inner_dim, list) for inner_dim in dataset.dims]):
+                required = True
             else:
                 required = False
 

nwb_linkml/adapters/group.py

@@ -6,7 +6,7 @@ from typing import List
 from linkml_runtime.linkml_model import ClassDefinition, SlotDefinition
 
 from nwb_schema_language import Dataset, Group, ReferenceDtype, CompoundDtype, DTypeType
-from nwb_linkml.adapters.classes import ClassAdapter
+from nwb_linkml.adapters.classes import ClassAdapter, camel_to_snake
 from nwb_linkml.adapters.dataset import DatasetAdapter
 from nwb_linkml.adapters.adapter import BuildResult
 from nwb_linkml.maps import QUANTITY_MAP
@@ -16,6 +16,17 @@ class GroupAdapter(ClassAdapter):
 
     def build(self) -> BuildResult:
 
+        # Handle container groups with only * quantity unnamed groups
+        if len(self.cls.groups) > 0 and \
+                all([self._check_if_container(g) for g in self.cls.groups]) and \
+                self.parent is not None:
+            return self.handle_container_group(self.cls)
+
+        # handle if we are a terminal container group without making a new class
+        if len(self.cls.groups) == 0 and \
+            self.cls.neurodata_type_inc is not None and \
+            self.parent is not None:
+            return self.handle_container_slot(self.cls)
 
         nested_res = self.build_subclasses()
         # we don't propagate slots up to the next level since they are meant for this
@@ -26,21 +37,78 @@ class GroupAdapter(ClassAdapter):
 
         return res
 
-    def handle_children(self, children: List[Group]) -> BuildResult:
+    def handle_container_group(self, cls: Group) -> BuildResult:
         """
         Make a special LinkML `children` slot that can
         have any number of the objects that are of `neurodata_type_inc` class
 
+        Examples:
+            - name: templates
+              groups:
+              - neurodata_type_inc: TimeSeries
+                doc: TimeSeries objects containing template data of presented stimuli.
+                quantity: '*'
+              - neurodata_type_inc: Images
+                doc: Images objects containing images of presented stimuli.
+                quantity: '*'
+
         Args:
             children (List[:class:`.Group`]): Child groups
 
         """
-        child_slot = SlotDefinition(
-            name='children',
-            multivalued=True,
-            any_of=[{'range': cls.neurodata_type_inc} for cls in children]
+
+        # don't build subgroups as their own classes, just make a slot
+        # that can contain them
+        if not self.cls.name:
+            name = 'children'
+        else:
+            name = cls.name
+
+        res = BuildResult(
+            slots = [SlotDefinition(
+                name=name,
+                multivalued=True,
+                description=cls.doc,
+                any_of=[{'range': subcls.neurodata_type_inc} for subcls in cls.groups]
+            )]
         )
-        return BuildResult(slots=[child_slot])
+        return res
+
+    def handle_container_slot(self, cls:Group) -> BuildResult:
+        """
+        Handle subgroups that contain arbitrarily numbered classes,
+
+        eg. *each* of the groups in
+
+        Examples:
+            - name: trials
+              neurodata_type_inc: TimeIntervals
+              doc: Repeated experimental events that have a logical grouping.
+              quantity: '?'
+            - name: invalid_times
+              neurodata_type_inc: TimeIntervals
+              doc: Time intervals that should be removed from analysis.
+              quantity: '?'
+            - neurodata_type_inc: TimeIntervals
+              doc: Optional additional table(s) for describing other experimental time intervals.
+              quantity: '*'
+        """
+        if not self.cls.name:
+            name = camel_to_snake(self.cls.neurodata_type_inc)
+        else:
+            name = cls.name
+
+        return BuildResult(
+            slots = [
+                SlotDefinition(
+                    name=name,
+                    range=self.cls.neurodata_type_inc,
+                    description=self.cls.doc,
+                    **QUANTITY_MAP[cls.quantity]
+                )
+            ]
+        )
+
 
     def build_subclasses(self) -> BuildResult:
         """
@@ -66,20 +134,8 @@ class GroupAdapter(ClassAdapter):
         # eg. a group can have multiple groups with `neurodata_type_inc`, no name, and quantity of *,
         # the group can then contain any number of groups of those included types as direct children
 
-        # group_res = BuildResult()
-        # children = []
-        # for group in self.cls.groups:
-        #     if not group.name and \
-        #         group.quantity == '*' and \
-        #         group.neurodata_type_inc:
-        #         children.append(group)
-        #     else:
-        #         group_adapter = GroupAdapter(cls=group, parent=self)
-        #         group_res += group_adapter.build()
-        #
-        # group_res += self.handle_children(children)
-
         group_res = BuildResult()
+
         for group in self.cls.groups:
             group_adapter = GroupAdapter(cls=group, parent=self)
             group_res += group_adapter.build()
@@ -87,3 +143,26 @@ class GroupAdapter(ClassAdapter):
         res = dataset_res + group_res
 
         return res
+
+    def _check_if_container(self, group:Group) -> bool:
+        """
+        Check if a given subgroup is a container subgroup,
+
+        ie. whether it's used to indicate a possible type for a child, as in:
+
+        - name: templates
+          groups:
+          - neurodata_type_inc: TimeSeries
+            doc: TimeSeries objects containing template data of presented stimuli.
+            quantity: '*'
+          - neurodata_type_inc: Images
+            doc: Images objects containing images of presented stimuli.
+            quantity: '*'
+        """
+        if not group.name and \
+            group.quantity == '*' and \
+            group.neurodata_type_inc:
+            return True
+        else:
+            return False
+

nwb_linkml/adapters/namespaces.py

@@ -74,6 +74,8 @@ class NamespacesAdapter(Adapter):
     def find_type_source(self, name:str) -> SchemaAdapter:
         """
         Given some neurodata_type_inc, find the schema that it's defined in.
+
+        Rather than returning as soon as a match is found, check all
         """
         # First check within the main schema
         internal_matches = []
@@ -82,6 +84,12 @@ class NamespacesAdapter(Adapter):
             if name in class_names:
                 internal_matches.append(schema)
 
+        if len(internal_matches) > 1:
+            raise KeyError(
+                f"Found multiple schemas in namespace that define {name}:\ninternal: {pformat(internal_matches)}\nimported:{pformat(import_matches)}")
+        elif len(internal_matches) == 1:
+            return internal_matches[0]
+
         import_matches = []
         for imported_ns in self.imported:
             for schema in imported_ns.schemas:
@@ -89,12 +97,10 @@ class NamespacesAdapter(Adapter):
                 if name in class_names:
                     import_matches.append(schema)
 
-        all_matches = [*internal_matches, *import_matches]
-
-        if len(all_matches)>1:
+        if len(import_matches)>1:
             raise KeyError(f"Found multiple schemas in namespace that define {name}:\ninternal: {pformat(internal_matches)}\nimported:{pformat(import_matches)}")
-        elif len(all_matches) == 1:
-            return all_matches[0]
+        elif len(import_matches) == 1:
+            return import_matches[0]
         else:
             raise KeyError(f"No schema found that define {name}")
 

nwb_linkml/adapters/schema.py

@@ -2,10 +2,10 @@
 Since NWB doesn't necessarily have a term for a single nwb schema file, we're going
 to call them "schema" objects
 """
-
-from typing import Optional, List, TYPE_CHECKING
+import pdb
+from typing import Optional, List, TYPE_CHECKING, Type
 from pathlib import Path
-from pydantic import Field
+from pydantic import Field, PrivateAttr
 
 from nwb_linkml.adapters.adapter import Adapter, BuildResult
 from nwb_linkml.adapters.dataset import DatasetAdapter
@@ -21,7 +21,7 @@ from linkml_runtime.linkml_model import SchemaDefinition
 
 class SplitSchema(NamedTuple):
     main: BuildResult
-    split: BuildResult
+    split: Optional[BuildResult]
 
 class SchemaAdapter(Adapter):
     """
@@ -38,6 +38,7 @@ class SchemaAdapter(Adapter):
         True,
         description="Split anonymous subclasses into a separate schema file"
    )
+    _created_classes: List[Type[Group | Dataset]] = PrivateAttr(default_factory=list)
 
     @property
     def name(self) -> str:
@@ -118,7 +119,8 @@ class SchemaAdapter(Adapter):
         # need to mutually import the two schemas because the subclasses
         # could refer to the main classes
         main_imports = imports
-        main_imports.append(split_sch_name)
+        if len(split_classes)>0:
+            main_imports.append(split_sch_name)
         imports.append(self.name)
         main_sch = SchemaDefinition(
             name=self.name,
@@ -128,6 +130,7 @@ class SchemaAdapter(Adapter):
             slots=classes.slots,
             types=classes.types
         )
+
         split_sch = SchemaDefinition(
             name=split_sch_name,
             id=split_sch_name,
@@ -136,17 +139,23 @@ class SchemaAdapter(Adapter):
             slots=classes.slots,
             types=classes.types
         )
-        res = BuildResult(
-            schemas=[main_sch, split_sch]
-        )
+        if len(split_classes) > 0:
+            res = BuildResult(
+                schemas=[main_sch, split_sch]
+            )
+        else:
+            res = BuildResult(
+                schemas=[main_sch]
+            )
         return res
 
 
 
     @property
-    def created_classes(self) -> List[Group|Dataset]:
-        classes = [t for t in self.walk_types([self.groups, self.datasets], (Group, Dataset)) if t.neurodata_type_def is not None]
-        return classes
+    def created_classes(self) -> List[Type[Group | Dataset]]:
+        if len(self._created_classes) == 0:
+            self._created_classes = [t for t in self.walk_types([self.groups, self.datasets], (Group, Dataset)) if t.neurodata_type_def is not None]
+        return self._created_classes
 
     @property
     def needed_imports(self) -> List[str]:
@@ -164,5 +173,3 @@ class SchemaAdapter(Adapter):
         return need
 
 
-
-

nwb_linkml/generators/pydantic.py

@@ -131,6 +131,9 @@ class {{ c.name }}
     {{attr.name}}: {{ attr.annotations['python_range'].value }} = Field(
     {%- if predefined_slot_values[c.name][attr.name] -%}
         {{ predefined_slot_values[c.name][attr.name] }}
+        {%- if attr.equals_string -%}
+        , const=True
+        {%- endif -%} 
     {%- elif attr.required -%}
         ...
     {%- else -%}
@@ -182,6 +185,10 @@ class NWBPydanticGenerator(PydanticGenerator):
             for slot_name, slot in cls.attributes.items():
                 if slot.range in all_classes:
                     needed_classes.append(slot.range)
+                if slot.any_of:
+                    for any_slot_range in slot.any_of:
+                        if any_slot_range.range in all_classes:
+                            needed_classes.append(any_slot_range.range)
 
         needed_classes = [cls for cls in set(needed_classes) if cls is not None]
         imports = {}
@@ -245,16 +252,16 @@ class NWBPydanticGenerator(PydanticGenerator):
             if not base_range_subsumes_any_of:
                 raise ValueError("Slot cannot have both range and any_of defined")
 
-    def _get_numpy_slot_range(self, cls:ClassDefinition) -> str:
+    def _make_npytyping_range(self, attrs: Dict[str, SlotDefinition]) -> str:
         # slot always starts with...
-        prefix='NDArray['
+        prefix = 'NDArray['
 
         # and then we specify the shape:
         shape_prefix = 'Shape["'
 
         # using the cardinality from the attributes
         dim_pieces = []
-        for attr in cls.attributes.values():
+        for attr in attrs.values():
 
             if attr.maximum_cardinality:
                 shape_part = str(attr.maximum_cardinality)
@@ -271,16 +278,41 @@ class NWBPydanticGenerator(PydanticGenerator):
 
         # all dimensions should be the same dtype
         try:
-            dtype = flat_to_npytyping[list(cls.attributes.values())[0].range]
+            dtype = flat_to_npytyping[list(attrs.values())[0].range]
         except KeyError as e:
             warnings.warn(e)
-            range = list(cls.attributes.values())[0].range
+            range = list(attrs.values())[0].range
             return f'List[{range}] | {range}'
         suffix = "]"
 
         slot = ''.join([prefix, shape_prefix, dimension, shape_suffix, dtype, suffix])
         return slot
 
+    def _get_numpy_slot_range(self, cls:ClassDefinition) -> str:
+        # if none of the dimensions are optional, we just have one possible array shape
+        if all([s.required for s in cls.attributes.values()]):
+            return self._make_npytyping_range(cls.attributes)
+        # otherwise we need to make permutations
+        # but not all permutations, because we typically just want to be able to exlude the last possible dimensions
+        # the array classes should always be well-defined where the optional dimensions are at the end, so
+        requireds = {k:v for k,v in cls.attributes.items() if v.required}
+        optionals = [(k,v) for k, v in cls.attributes.items() if not v.required]
+
+        annotations = []
+        if len(requireds) > 0:
+            # first the base case
+            annotations.append(self._make_npytyping_range(requireds))
+        # then add back each optional dimension
+        for i in range(len(optionals)):
+            attrs = {**requireds, **{k:v for k, v in optionals[0:i+1]}}
+            annotations.append(self._make_npytyping_range(attrs))
+
+        # now combine with a union:
+        union = "Union[\n" + ' '*8
+        union += (',\n' + ' '*8).join(annotations)
+        union += '\n' + ' '*4 + ']'
+        return union
+
 
     def sort_classes(self, clist: List[ClassDefinition], imports:List[str]) -> List[ClassDefinition]:
         """

nwb_linkml/maps/dtype.py

@@ -24,7 +24,7 @@ flat_to_linkml = {
     "utf_8" : "string",
     "ascii" : "string",
     "bool" : "boolean",
-    "isodatetime" : "date"
+    "isodatetime" : "datetime"
 }
 """
 Map between the flat data types and the simpler linkml base types

nwb_linkml/models/core.py

@@ -15,13 +15,9 @@ else:
 metamodel_version = "None"
 version = "2.6.0-alpha"
 
-class WeakRefShimBaseModel(BaseModel):
-   __slots__ = '__weakref__'
-
-class ConfiguredBaseModel(WeakRefShimBaseModel,
+class ConfiguredBaseModel(BaseModel,
                 validate_assignment = True,
-                validate_all = True,
-                underscore_attrs_are_private = True,
+                validate_default = True,
                 extra = 'forbid',
                 arbitrary_types_allowed = True,
                 use_enum_values = True):
@@ -29,5 +25,6 @@ class ConfiguredBaseModel(WeakRefShimBaseModel,
 
 
 
-# Update forward refs
-# see https://pydantic-docs.helpmanual.io/usage/postponed_annotations/
+# Model rebuild
+# see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
+    

nwb_linkml/models/core_nwb_base.py

@@ -11,39 +11,32 @@ else:
     from typing_extensions import Literal
 
 
-from .core_nwb_base_include import (
-    TimeSeriesSync,
-    TimeSeriesControlDescription,
-    # ImageReferencesArray,
-    ImageArray,
-    TimeSeriesControl,
-    TimeSeriesData,
-    # ImagesOrderOfImages,
-    TimeSeriesTimestamps,
-    TimeSeriesStartingTime
+from .hdmf_common_table import (
+    DynamicTable,
+    VectorData
 )
 
 from .hdmf_common_base import (
-    Container,
-    Data
+    Data,
+    Container
 )
 
-# from .hdmf_common_table import (
-#     DynamicTable,
-#     VectorData
-# )
+from .core_nwb_base_include import (
+    TimeSeriesStartingTime,
+    ImageArray,
+    ImageReferencesArray,
+    TimeSeriesSync,
+    ImagesOrderOfImages,
+    TimeSeriesData
+)
 
 
 metamodel_version = "None"
 version = "None"
 
-class WeakRefShimBaseModel(BaseModel):
-   __slots__ = '__weakref__'
-
-class ConfiguredBaseModel(WeakRefShimBaseModel,
+class ConfiguredBaseModel(BaseModel,
                 validate_assignment = True,
-                validate_all = True,
-                underscore_attrs_are_private = True,
+                validate_default = True,
                 extra = 'forbid',
                 arbitrary_types_allowed = True,
                 use_enum_values = True):
@@ -54,88 +47,104 @@ class NWBData(Data):
     """
     An abstract data type for a dataset.
     """
-    None
+    name: str = Field(...)
     
 
-# class TimeSeriesReferenceVectorData(VectorData):
-#     """
-#     Column storing references to a TimeSeries (rows). For each TimeSeries this VectorData column stores the start_index and count to indicate the range in time to be selected as well as an object reference to the TimeSeries.
-#     """
-#     description: Optional[str] = Field(None, description="""Description of what these vectors represent.""")
-#     array: Optional[NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], Any]] = Field(None)
-#
+class TimeSeriesReferenceVectorData(VectorData):
+    """
+    Column storing references to a TimeSeries (rows). For each TimeSeries this VectorData column stores the start_index and count to indicate the range in time to be selected as well as an object reference to the TimeSeries.
+    """
+    name: str = Field(...)
+    description: Optional[str] = Field(None, description="""Description of what these vectors represent.""")
+    array: Optional[Union[
+        NDArray[Shape["* dim0"], Any],
+        NDArray[Shape["* dim0, * dim1"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], Any]
+    ]] = Field(None)
+    
 
 class Image(NWBData):
     """
     An abstract data type for an image. Shape can be 2-D (x, y), or 3-D where the third dimension can have three or four elements, e.g. (x, y, (r, g, b)) or (x, y, (r, g, b, a)).
     """
+    name: str = Field(...)
     resolution: Optional[float] = Field(None, description="""Pixel resolution of the image, in pixels per centimeter.""")
     description: Optional[str] = Field(None, description="""Description of the image.""")
-    array: Optional[NDArray[Shape["* x, * y, 3 r_g_b, 4 r_g_b_a"], Number]] = Field(None)
+    array: Optional[Union[
+        NDArray[Shape["* x, * y"], Number],
+        NDArray[Shape["* x, * y, 3 r_g_b"], Number],
+        NDArray[Shape["* x, * y, 3 r_g_b, 4 r_g_b_a"], Number]
+    ]] = Field(None)
     
 
-# class ImageReferences(NWBData):
-#     """
-#     Ordered dataset of references to Image objects.
-#     """
-#     array: Optional[List[Image] | Image] = Field(None)
-#
+class ImageReferences(NWBData):
+    """
+    Ordered dataset of references to Image objects.
+    """
+    name: str = Field(...)
+    array: Optional[List[Image] | Image] = Field(None)
+    
 
 class NWBContainer(Container):
     """
     An abstract data type for a generic container storing collections of data and metadata. Base type for all data and metadata containers.
     """
-    None
+    name: str = Field(...)
     
 
 class NWBDataInterface(NWBContainer):
     """
     An abstract data type for a generic container storing collections of data, as opposed to metadata.
     """
-    None
+    name: str = Field(...)
     
 
 class TimeSeries(NWBDataInterface):
     """
     General purpose time series.
     """
+    name: str = Field(...)
     description: Optional[str] = Field(None, description="""Description of the time series.""")
     comments: Optional[str] = Field(None, description="""Human-readable comments about the TimeSeries. This second descriptive field can be used to store additional information, or descriptive information if the primary description field is populated with a computer-readable string.""")
     data: TimeSeriesData = Field(..., description="""Data values. Data can be in 1-D, 2-D, 3-D, or 4-D. The first dimension should always represent time. This can also be used to store binary data (e.g., image frames). This can also be a link to data stored in an external file.""")
     starting_time: Optional[TimeSeriesStartingTime] = Field(None, description="""Timestamp of the first sample in seconds. When timestamps are uniformly spaced, the timestamp of the first sample can be specified and all subsequent ones calculated from the sampling rate attribute.""")
-    timestamps: Optional[TimeSeriesTimestamps] = Field(None, description="""Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time.""")
-    control: Optional[TimeSeriesControl] = Field(None, description="""Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data.""")
-    control_description: Optional[TimeSeriesControlDescription] = Field(None, description="""Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0.""")
+    timestamps: Optional[List[float]] = Field(default_factory=list, description="""Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time.""")
+    control: Optional[List[int]] = Field(default_factory=list, description="""Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data.""")
+    control_description: Optional[List[str]] = Field(default_factory=list, description="""Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0.""")
     sync: Optional[TimeSeriesSync] = Field(None, description="""Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of 'sync' are mostly for archival purposes.""")
     
 
-# class ProcessingModule(NWBContainer):
-#     """
-#     A collection of processed data.
-#     """
-#     description: Optional[str] = Field(None, description="""Description of this collection of processed data.""")
-#     NWBDataInterface: Optional[List[NWBDataInterface]] = Field(default_factory=list, description="""Data objects stored in this collection.""")
-#     DynamicTable: Optional[List[DynamicTable]] = Field(default_factory=list, description="""Tables stored in this collection.""")
-#
-
-# class Images(NWBDataInterface):
-#     """
-#     A collection of images with an optional way to specify the order of the images using the \"order_of_images\" dataset. An order must be specified if the images are referenced by index, e.g., from an IndexSeries.
-#     """
-#     description: Optional[str] = Field(None, description="""Description of this collection of images.""")
-#     Image: List[Image] = Field(default_factory=list, description="""Images stored in this collection.""")
-#     order_of_images: Optional[ImagesOrderOfImages] = Field(None, description="""Ordered dataset of references to Image objects stored in the parent group. Each Image object in the Images group should be stored once and only once, so the dataset should have the same length as the number of images.""")
-#
+class ProcessingModule(NWBContainer):
+    """
+    A collection of processed data.
+    """
+    name: str = Field(...)
+    description: Optional[str] = Field(None, description="""Description of this collection of processed data.""")
+    nwb_data_interface: Optional[List[NWBDataInterface]] = Field(default_factory=list, description="""Data objects stored in this collection.""")
+    dynamic_table: Optional[List[DynamicTable]] = Field(default_factory=list, description="""Tables stored in this collection.""")
     
 
-# Update forward refs
-# see https://pydantic-docs.helpmanual.io/usage/postponed_annotations/
-NWBData.update_forward_refs()
-# TimeSeriesReferenceVectorData.update_forward_refs()
-Image.update_forward_refs()
-# ImageReferences.update_forward_refs()
-NWBContainer.update_forward_refs()
-NWBDataInterface.update_forward_refs()
-TimeSeries.update_forward_refs()
-# ProcessingModule.update_forward_refs()
-# Images.update_forward_refs()
+class Images(NWBDataInterface):
+    """
+    A collection of images with an optional way to specify the order of the images using the \"order_of_images\" dataset. An order must be specified if the images are referenced by index, e.g., from an IndexSeries.
+    """
+    name: str = Field(...)
+    description: Optional[str] = Field(None, description="""Description of this collection of images.""")
+    Image: List[Image] = Field(default_factory=list, description="""Images stored in this collection.""")
+    order_of_images: Optional[ImagesOrderOfImages] = Field(None, description="""Ordered dataset of references to Image objects stored in the parent group. Each Image object in the Images group should be stored once and only once, so the dataset should have the same length as the number of images.""")
+    
+
+
+# Model rebuild
+# see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
+NWBData.model_rebuild()
+TimeSeriesReferenceVectorData.model_rebuild()
+Image.model_rebuild()
+ImageReferences.model_rebuild()
+NWBContainer.model_rebuild()
+NWBDataInterface.model_rebuild()
+TimeSeries.model_rebuild()
+ProcessingModule.model_rebuild()
+Images.model_rebuild()
+    

nwb_linkml/models/core_nwb_base_include.py

@@ -15,22 +15,18 @@ from .nwb_language import (
     Arraylike
 )
 
-# from .core_nwb_base import (
-#     ImageReferences,
-#     Image
-# )
+from .core_nwb_base import (
+    ImageReferences,
+    Image
+)
 
 
 metamodel_version = "None"
 version = "None"
 
-class WeakRefShimBaseModel(BaseModel):
-   __slots__ = '__weakref__'
-
-class ConfiguredBaseModel(WeakRefShimBaseModel,
+class ConfiguredBaseModel(BaseModel,
                 validate_assignment = True,
-                validate_all = True,
-                underscore_attrs_are_private = True,
+                validate_default = True,
                 extra = 'forbid',
                 arbitrary_types_allowed = True,
                 use_enum_values = True):
@@ -45,21 +41,27 @@ class ImageArray(Arraylike):
     r_g_b_a: Optional[float] = Field(None)
     
 
-# class ImageReferencesArray(Arraylike):
-#
-#     num_images: Image = Field(...)
+class ImageReferencesArray(Arraylike):
+    
+    num_images: Image = Field(...)
     
 
 class TimeSeriesData(ConfiguredBaseModel):
     """
     Data values. Data can be in 1-D, 2-D, 3-D, or 4-D. The first dimension should always represent time. This can also be used to store binary data (e.g., image frames). This can also be a link to data stored in an external file.
     """
+    name: str = Field("data", const=True)
     conversion: Optional[float] = Field(None, description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""")
     offset: Optional[float] = Field(None, description="""Scalar to add to the data after scaling by 'conversion' to finalize its coercion to the specified 'unit'. Two common examples of this include (a) data stored in an unsigned type that requires a shift after scaling to re-center the data, and (b) specialized recording devices that naturally cause a scalar offset with respect to the true units.""")
     resolution: Optional[float] = Field(None, description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""")
     unit: Optional[str] = Field(None, description="""Base unit of measurement for working with the data. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion' and add 'offset'.""")
     continuity: Optional[str] = Field(None, description="""Optionally describe the continuity of the data. Can be \"continuous\", \"instantaneous\", or \"step\". For example, a voltage trace would be \"continuous\", because samples are recorded from a continuous process. An array of lick times would be \"instantaneous\", because the data represents distinct moments in time. Times of image presentations would be \"step\" because the picture remains the same until the next timepoint. This field is optional, but is useful in providing information about the underlying data. It may inform the way this data is interpreted, the way it is visualized, and what analysis methods are applicable.""")
-    array: Optional[NDArray[Shape["* num_times, ..."], Number]] = Field(None)
+    array: Optional[Union[
+        NDArray[Shape["* num_times"], Any],
+        NDArray[Shape["* num_times, * num_DIM2"], Any],
+        NDArray[Shape["* num_times, * num_DIM2, * num_DIM3"], Any],
+        NDArray[Shape["* num_times, * num_DIM2, * num_DIM3, * num_DIM4"], Any]
+    ]] = Field(None)
     
 
 class TimeSeriesDataArray(Arraylike):
@@ -74,57 +76,34 @@ class TimeSeriesStartingTime(ConfiguredBaseModel):
     """
     Timestamp of the first sample in seconds. When timestamps are uniformly spaced, the timestamp of the first sample can be specified and all subsequent ones calculated from the sampling rate attribute.
     """
+    name: str = Field("starting_time", const=True)
     rate: Optional[float] = Field(None, description="""Sampling rate, in Hz.""")
     unit: Optional[str] = Field(None, description="""Unit of measurement for time, which is fixed to 'seconds'.""")
     
 
-class TimeSeriesTimestamps(ConfiguredBaseModel):
-    """
-    Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time.
-    """
-    interval: Optional[int] = Field(None, description="""Value is '1'""")
-    unit: Optional[str] = Field(None, description="""Unit of measurement for timestamps, which is fixed to 'seconds'.""")
-    timestamps: Optional[List[float]] = Field(default_factory=list, description="""Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time.""")
-    
-
-class TimeSeriesControl(ConfiguredBaseModel):
-    """
-    Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data.
-    """
-    control: Optional[List[int]] = Field(default_factory=list, description="""Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data.""")
-    
-
-class TimeSeriesControlDescription(ConfiguredBaseModel):
-    """
-    Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0.
-    """
-    control_description: Optional[List[str]] = Field(default_factory=list, description="""Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0.""")
-    
-
 class TimeSeriesSync(ConfiguredBaseModel):
     """
     Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of 'sync' are mostly for archival purposes.
     """
-    None
+    name: str = Field("sync", const=True)
     
 
-# class ImagesOrderOfImages(ImageReferences):
-#     """
-#     Ordered dataset of references to Image objects stored in the parent group. Each Image object in the Images group should be stored once and only once, so the dataset should have the same length as the number of images.
-#     """
-#     array: Optional[List[Image] | Image] = Field(None)
+class ImagesOrderOfImages(ImageReferences):
+    """
+    Ordered dataset of references to Image objects stored in the parent group. Each Image object in the Images group should be stored once and only once, so the dataset should have the same length as the number of images.
+    """
+    name: str = Field("order_of_images", const=True)
+    array: Optional[List[Image] | Image] = Field(None)
     
 
 
-# Update forward refs
-# see https://pydantic-docs.helpmanual.io/usage/postponed_annotations/
-ImageArray.update_forward_refs()
-# ImageReferencesArray.update_forward_refs()
-TimeSeriesData.update_forward_refs()
-TimeSeriesDataArray.update_forward_refs()
-TimeSeriesStartingTime.update_forward_refs()
-TimeSeriesTimestamps.update_forward_refs()
-TimeSeriesControl.update_forward_refs()
-TimeSeriesControlDescription.update_forward_refs()
-TimeSeriesSync.update_forward_refs()
-# ImagesOrderOfImages.update_forward_refs()
+# Model rebuild
+# see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
+ImageArray.model_rebuild()
+ImageReferencesArray.model_rebuild()
+TimeSeriesData.model_rebuild()
+TimeSeriesDataArray.model_rebuild()
+TimeSeriesStartingTime.model_rebuild()
+TimeSeriesSync.model_rebuild()
+ImagesOrderOfImages.model_rebuild()
+    

nwb_linkml/models/core_nwb_behavior.py

@@ -11,15 +11,15 @@ else:
     from typing_extensions import Literal
 
 
-from .core_nwb_behavior_include import (
-    SpatialSeriesData
-)
-
 from .core_nwb_base import (
     TimeSeries,
     NWBDataInterface
 )
 
+from .core_nwb_behavior_include import (
+    SpatialSeriesData
+)
+
 from .core_nwb_misc import (
     IntervalSeries
 )
@@ -28,13 +28,9 @@ from .core_nwb_misc import (
 metamodel_version = "None"
 version = "None"
 
-class WeakRefShimBaseModel(BaseModel):
-   __slots__ = '__weakref__'
-
-class ConfiguredBaseModel(WeakRefShimBaseModel,
+class ConfiguredBaseModel(BaseModel,
                 validate_assignment = True,
-                validate_all = True,
-                underscore_attrs_are_private = True,
+                validate_default = True,
                 extra = 'forbid',
                 arbitrary_types_allowed = True,
                 use_enum_values = True):
@@ -45,14 +41,15 @@ class SpatialSeries(TimeSeries):
     """
     Direction, e.g., of gaze or travel, or position. The TimeSeries::data field is a 2D array storing position or direction relative to some reference frame. Array structure: [num measurements] [num dimensions]. Each SpatialSeries has a text dataset reference_frame that indicates the zero-position, or the zero-axes for direction. For example, if representing gaze direction, 'straight-ahead' might be a specific pixel on the monitor, or some other point in space. For position data, the 0,0 point might be the top-left corner of an enclosure, as viewed from the tracking camera. The unit of data will indicate how to interpret SpatialSeries values.
     """
+    name: str = Field(...)
     data: SpatialSeriesData = Field(..., description="""1-D or 2-D array storing position or direction relative to some reference frame.""")
     reference_frame: Optional[str] = Field(None, description="""Description defining what exactly 'straight-ahead' means.""")
     description: Optional[str] = Field(None, description="""Description of the time series.""")
     comments: Optional[str] = Field(None, description="""Human-readable comments about the TimeSeries. This second descriptive field can be used to store additional information, or descriptive information if the primary description field is populated with a computer-readable string.""")
     starting_time: Optional[TimeSeriesStartingTime] = Field(None, description="""Timestamp of the first sample in seconds. When timestamps are uniformly spaced, the timestamp of the first sample can be specified and all subsequent ones calculated from the sampling rate attribute.""")
-    timestamps: Optional[TimeSeriesTimestamps] = Field(None, description="""Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time.""")
-    control: Optional[TimeSeriesControl] = Field(None, description="""Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data.""")
-    control_description: Optional[TimeSeriesControlDescription] = Field(None, description="""Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0.""")
+    timestamps: Optional[List[float]] = Field(default_factory=list, description="""Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time.""")
+    control: Optional[List[int]] = Field(default_factory=list, description="""Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data.""")
+    control_description: Optional[List[str]] = Field(default_factory=list, description="""Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0.""")
     sync: Optional[TimeSeriesSync] = Field(None, description="""Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of 'sync' are mostly for archival purposes.""")
     
 
@@ -60,59 +57,67 @@ class BehavioralEpochs(NWBDataInterface):
     """
     TimeSeries for storing behavioral epochs.  The objective of this and the other two Behavioral interfaces (e.g. BehavioralEvents and BehavioralTimeSeries) is to provide generic hooks for software tools/scripts. This allows a tool/script to take the output one specific interface (e.g., UnitTimes) and plot that data relative to another data modality (e.g., behavioral events) without having to define all possible modalities in advance. Declaring one of these interfaces means that one or more TimeSeries of the specified type is published. These TimeSeries should reside in a group having the same name as the interface. For example, if a BehavioralTimeSeries interface is declared, the module will have one or more TimeSeries defined in the module sub-group 'BehavioralTimeSeries'. BehavioralEpochs should use IntervalSeries. BehavioralEvents is used for irregular events. BehavioralTimeSeries is for continuous data.
     """
-    IntervalSeries: Optional[List[IntervalSeries]] = Field(default_factory=list, description="""IntervalSeries object containing start and stop times of epochs.""")
+    name: str = Field(...)
+    interval_series: Optional[List[IntervalSeries]] = Field(default_factory=list, description="""IntervalSeries object containing start and stop times of epochs.""")
     
 
 class BehavioralEvents(NWBDataInterface):
     """
     TimeSeries for storing behavioral events. See description of <a href=\"#BehavioralEpochs\">BehavioralEpochs</a> for more details.
     """
-    TimeSeries: Optional[List[TimeSeries]] = Field(default_factory=list, description="""TimeSeries object containing behavioral events.""")
+    name: str = Field(...)
+    time_series: Optional[List[TimeSeries]] = Field(default_factory=list, description="""TimeSeries object containing behavioral events.""")
     
 
 class BehavioralTimeSeries(NWBDataInterface):
     """
     TimeSeries for storing Behavoioral time series data. See description of <a href=\"#BehavioralEpochs\">BehavioralEpochs</a> for more details.
     """
-    TimeSeries: Optional[List[TimeSeries]] = Field(default_factory=list, description="""TimeSeries object containing continuous behavioral data.""")
+    name: str = Field(...)
+    time_series: Optional[List[TimeSeries]] = Field(default_factory=list, description="""TimeSeries object containing continuous behavioral data.""")
     
 
 class PupilTracking(NWBDataInterface):
     """
     Eye-tracking data, representing pupil size.
     """
-    TimeSeries: List[TimeSeries] = Field(default_factory=list, description="""TimeSeries object containing time series data on pupil size.""")
+    name: str = Field(...)
+    time_series: List[TimeSeries] = Field(default_factory=list, description="""TimeSeries object containing time series data on pupil size.""")
     
 
 class EyeTracking(NWBDataInterface):
     """
     Eye-tracking data, representing direction of gaze.
     """
-    SpatialSeries: Optional[List[SpatialSeries]] = Field(default_factory=list, description="""SpatialSeries object containing data measuring direction of gaze.""")
+    name: str = Field(...)
+    spatial_series: Optional[List[SpatialSeries]] = Field(default_factory=list, description="""SpatialSeries object containing data measuring direction of gaze.""")
     
 
 class CompassDirection(NWBDataInterface):
     """
     With a CompassDirection interface, a module publishes a SpatialSeries object representing a floating point value for theta. The SpatialSeries::reference_frame field should indicate what direction corresponds to 0 and which is the direction of rotation (this should be clockwise). The si_unit for the SpatialSeries should be radians or degrees.
     """
-    SpatialSeries: Optional[List[SpatialSeries]] = Field(default_factory=list, description="""SpatialSeries object containing direction of gaze travel.""")
+    name: str = Field(...)
+    spatial_series: Optional[List[SpatialSeries]] = Field(default_factory=list, description="""SpatialSeries object containing direction of gaze travel.""")
     
 
 class Position(NWBDataInterface):
     """
     Position data, whether along the x, x/y or x/y/z axis.
     """
-    SpatialSeries: List[SpatialSeries] = Field(default_factory=list, description="""SpatialSeries object containing position data.""")
+    name: str = Field(...)
+    spatial_series: List[SpatialSeries] = Field(default_factory=list, description="""SpatialSeries object containing position data.""")
     
 
 
-# Update forward refs
-# see https://pydantic-docs.helpmanual.io/usage/postponed_annotations/
-SpatialSeries.update_forward_refs()
-BehavioralEpochs.update_forward_refs()
-BehavioralEvents.update_forward_refs()
-BehavioralTimeSeries.update_forward_refs()
-PupilTracking.update_forward_refs()
-EyeTracking.update_forward_refs()
-CompassDirection.update_forward_refs()
-Position.update_forward_refs()
+# Model rebuild
+# see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
+SpatialSeries.model_rebuild()
+BehavioralEpochs.model_rebuild()
+BehavioralEvents.model_rebuild()
+BehavioralTimeSeries.model_rebuild()
+PupilTracking.model_rebuild()
+EyeTracking.model_rebuild()
+CompassDirection.model_rebuild()
+Position.model_rebuild()
+    

nwb_linkml/models/core_nwb_behavior_include.py

@@ -19,13 +19,9 @@ from .nwb_language import (
 metamodel_version = "None"
 version = "None"
 
-class WeakRefShimBaseModel(BaseModel):
-   __slots__ = '__weakref__'
-
-class ConfiguredBaseModel(WeakRefShimBaseModel,
+class ConfiguredBaseModel(BaseModel,
                 validate_assignment = True,
-                validate_all = True,
-                underscore_attrs_are_private = True,
+                validate_default = True,
                 extra = 'forbid',
                 arbitrary_types_allowed = True,
                 use_enum_values = True):
@@ -36,8 +32,14 @@ class SpatialSeriesData(ConfiguredBaseModel):
     """
     1-D or 2-D array storing position or direction relative to some reference frame.
     """
+    name: str = Field("data", const=True)
     unit: Optional[str] = Field(None, description="""Base unit of measurement for working with the data. The default value is 'meters'. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion' and add 'offset'.""")
-    array: Optional[NDArray[Shape["* num_times, 1 x, 2 x_y, 3 x_y_z"], Number]] = Field(None)
+    array: Optional[Union[
+        NDArray[Shape["* num_times"], Number],
+        NDArray[Shape["* num_times, 1 x"], Number],
+        NDArray[Shape["* num_times, 1 x, 2 x_y"], Number],
+        NDArray[Shape["* num_times, 1 x, 2 x_y, 3 x_y_z"], Number]
+    ]] = Field(None)
     
 
 class SpatialSeriesDataArray(Arraylike):
@@ -49,7 +51,8 @@ class SpatialSeriesDataArray(Arraylike):
     
 
 
-# Update forward refs
-# see https://pydantic-docs.helpmanual.io/usage/postponed_annotations/
-SpatialSeriesData.update_forward_refs()
-SpatialSeriesDataArray.update_forward_refs()
+# Model rebuild
+# see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
+SpatialSeriesData.model_rebuild()
+SpatialSeriesDataArray.model_rebuild()
+    

nwb_linkml/models/core_nwb_device.py

@@ -19,13 +19,9 @@ from .core_nwb_base import (
 metamodel_version = "None"
 version = "None"
 
-class WeakRefShimBaseModel(BaseModel):
-   __slots__ = '__weakref__'
-
-class ConfiguredBaseModel(WeakRefShimBaseModel,
+class ConfiguredBaseModel(BaseModel,
                 validate_assignment = True,
-                validate_all = True,
-                underscore_attrs_are_private = True,
+                validate_default = True,
                 extra = 'forbid',
                 arbitrary_types_allowed = True,
                 use_enum_values = True):
@@ -36,11 +32,13 @@ class Device(NWBContainer):
     """
     Metadata about a data acquisition device, e.g., recording system, electrode, microscope.
     """
+    name: str = Field(...)
     description: Optional[str] = Field(None, description="""Description of the device (e.g., model, firmware version, processing software version, etc.) as free-form text.""")
     manufacturer: Optional[str] = Field(None, description="""The name of the manufacturer of the device.""")
     
 
 
-# Update forward refs
-# see https://pydantic-docs.helpmanual.io/usage/postponed_annotations/
-Device.update_forward_refs()
+# Model rebuild
+# see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
+Device.model_rebuild()
+    

nwb_linkml/models/core_nwb_device_include.py

@@ -1,33 +0,0 @@
-from __future__ import annotations
-from datetime import datetime, date
-from enum import Enum
-from typing import List, Dict, Optional, Any, Union
-from pydantic import BaseModel as BaseModel, Field
-from nptyping import NDArray, Shape, Float, Float32, Double, Float64, LongLong, Int64, Int, Int32, Int16, Short, Int8, UInt, UInt32, UInt16, UInt8, UInt64, Number, String, Unicode, Unicode, Unicode, String, Bool, Datetime64
-import sys
-if sys.version_info >= (3, 8):
-    from typing import Literal
-else:
-    from typing_extensions import Literal
-
-
-
-metamodel_version = "None"
-version = "None"
-
-class WeakRefShimBaseModel(BaseModel):
-   __slots__ = '__weakref__'
-
-class ConfiguredBaseModel(WeakRefShimBaseModel,
-                validate_assignment = True,
-                validate_all = True,
-                underscore_attrs_are_private = True,
-                extra = 'forbid',
-                arbitrary_types_allowed = True,
-                use_enum_values = True):
-    pass
-
-
-
-# Update forward refs
-# see https://pydantic-docs.helpmanual.io/usage/postponed_annotations/

nwb_linkml/models/core_nwb_ecephys.py

@@ -11,42 +11,29 @@ else:
     from typing_extensions import Literal
 
 
-from .core_nwb_ecephys_include import (
-    ClusteringPeakOverRms,
-    FeatureExtractionDescription,
-    FeatureExtractionFeatures,
-    EventDetectionSourceIdx,
-    ClusteringTimes,
-    SpikeEventSeriesTimestamps,
-    EventDetectionTimes,
-    ClusterWaveformsWaveformMean,
-    SpikeEventSeriesData,
-    FeatureExtractionTimes,
-    ClusteringNum,
-    ElectricalSeriesChannelConversion,
-    ClusterWaveformsWaveformSd,
-    ElectricalSeriesData,
-    ElectricalSeriesElectrodes,
-    FeatureExtractionElectrodes
-)
-
 from .core_nwb_base import (
     TimeSeries,
     NWBContainer,
     NWBDataInterface
 )
 
+from .core_nwb_ecephys_include import (
+    FeatureExtractionElectrodes,
+    ClusterWaveformsWaveformSd,
+    ClusterWaveformsWaveformMean,
+    SpikeEventSeriesData,
+    ElectricalSeriesElectrodes,
+    ElectricalSeriesData,
+    FeatureExtractionFeatures
+)
+
 
 metamodel_version = "None"
 version = "None"
 
-class WeakRefShimBaseModel(BaseModel):
-   __slots__ = '__weakref__'
-
-class ConfiguredBaseModel(WeakRefShimBaseModel,
+class ConfiguredBaseModel(BaseModel,
                 validate_assignment = True,
-                validate_all = True,
-                underscore_attrs_are_private = True,
+                validate_default = True,
                 extra = 'forbid',
                 arbitrary_types_allowed = True,
                 use_enum_values = True):
@@ -57,16 +44,17 @@ class ElectricalSeries(TimeSeries):
     """
     A time series of acquired voltage data from extracellular recordings. The data field is an int or float array storing data in volts. The first dimension should always represent time. The second dimension, if present, should represent channels.
     """
+    name: str = Field(...)
     filtering: Optional[str] = Field(None, description="""Filtering applied to all channels of the data. For example, if this ElectricalSeries represents high-pass-filtered data (also known as AP Band), then this value could be \"High-pass 4-pole Bessel filter at 500 Hz\". If this ElectricalSeries represents low-pass-filtered LFP data and the type of filter is unknown, then this value could be \"Low-pass filter at 300 Hz\". If a non-standard filter type is used, provide as much detail about the filter properties as possible.""")
     data: ElectricalSeriesData = Field(..., description="""Recorded voltage data.""")
     electrodes: ElectricalSeriesElectrodes = Field(..., description="""DynamicTableRegion pointer to the electrodes that this time series was generated from.""")
-    channel_conversion: Optional[ElectricalSeriesChannelConversion] = Field(None, description="""Channel-specific conversion factor. Multiply the data in the 'data' dataset by these values along the channel axis (as indicated by axis attribute) AND by the global conversion factor in the 'conversion' attribute of 'data' to get the data values in Volts, i.e, data in Volts = data * data.conversion * channel_conversion. This approach allows for both global and per-channel data conversion factors needed to support the storage of electrical recordings as native values generated by data acquisition systems. If this dataset is not present, then there is no channel-specific conversion factor, i.e. it is 1 for all channels.""")
+    channel_conversion: Optional[List[float]] = Field(default_factory=list, description="""Channel-specific conversion factor. Multiply the data in the 'data' dataset by these values along the channel axis (as indicated by axis attribute) AND by the global conversion factor in the 'conversion' attribute of 'data' to get the data values in Volts, i.e, data in Volts = data * data.conversion * channel_conversion. This approach allows for both global and per-channel data conversion factors needed to support the storage of electrical recordings as native values generated by data acquisition systems. If this dataset is not present, then there is no channel-specific conversion factor, i.e. it is 1 for all channels.""")
     description: Optional[str] = Field(None, description="""Description of the time series.""")
     comments: Optional[str] = Field(None, description="""Human-readable comments about the TimeSeries. This second descriptive field can be used to store additional information, or descriptive information if the primary description field is populated with a computer-readable string.""")
     starting_time: Optional[TimeSeriesStartingTime] = Field(None, description="""Timestamp of the first sample in seconds. When timestamps are uniformly spaced, the timestamp of the first sample can be specified and all subsequent ones calculated from the sampling rate attribute.""")
-    timestamps: Optional[TimeSeriesTimestamps] = Field(None, description="""Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time.""")
-    control: Optional[TimeSeriesControl] = Field(None, description="""Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data.""")
-    control_description: Optional[TimeSeriesControlDescription] = Field(None, description="""Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0.""")
+    timestamps: Optional[List[float]] = Field(default_factory=list, description="""Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time.""")
+    control: Optional[List[int]] = Field(default_factory=list, description="""Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data.""")
+    control_description: Optional[List[str]] = Field(default_factory=list, description="""Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0.""")
     sync: Optional[TimeSeriesSync] = Field(None, description="""Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of 'sync' are mostly for archival purposes.""")
     
 
@@ -74,16 +62,17 @@ class SpikeEventSeries(ElectricalSeries):
     """
     Stores snapshots/snippets of recorded spike events (i.e., threshold crossings). This may also be raw data, as reported by ephys hardware. If so, the TimeSeries::description field should describe how events were detected. All SpikeEventSeries should reside in a module (under EventWaveform interface) even if the spikes were reported and stored by hardware. All events span the same recording channels and store snapshots of equal duration. TimeSeries::data array structure: [num events] [num channels] [num samples] (or [num events] [num samples] for single electrode).
     """
+    name: str = Field(...)
     data: SpikeEventSeriesData = Field(..., description="""Spike waveforms.""")
-    timestamps: SpikeEventSeriesTimestamps = Field(..., description="""Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time. Timestamps are required for the events. Unlike for TimeSeries, timestamps are required for SpikeEventSeries and are thus re-specified here.""")
+    timestamps: List[float] = Field(default_factory=list, description="""Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time. Timestamps are required for the events. Unlike for TimeSeries, timestamps are required for SpikeEventSeries and are thus re-specified here.""")
     filtering: Optional[str] = Field(None, description="""Filtering applied to all channels of the data. For example, if this ElectricalSeries represents high-pass-filtered data (also known as AP Band), then this value could be \"High-pass 4-pole Bessel filter at 500 Hz\". If this ElectricalSeries represents low-pass-filtered LFP data and the type of filter is unknown, then this value could be \"Low-pass filter at 300 Hz\". If a non-standard filter type is used, provide as much detail about the filter properties as possible.""")
     electrodes: ElectricalSeriesElectrodes = Field(..., description="""DynamicTableRegion pointer to the electrodes that this time series was generated from.""")
-    channel_conversion: Optional[ElectricalSeriesChannelConversion] = Field(None, description="""Channel-specific conversion factor. Multiply the data in the 'data' dataset by these values along the channel axis (as indicated by axis attribute) AND by the global conversion factor in the 'conversion' attribute of 'data' to get the data values in Volts, i.e, data in Volts = data * data.conversion * channel_conversion. This approach allows for both global and per-channel data conversion factors needed to support the storage of electrical recordings as native values generated by data acquisition systems. If this dataset is not present, then there is no channel-specific conversion factor, i.e. it is 1 for all channels.""")
+    channel_conversion: Optional[List[float]] = Field(default_factory=list, description="""Channel-specific conversion factor. Multiply the data in the 'data' dataset by these values along the channel axis (as indicated by axis attribute) AND by the global conversion factor in the 'conversion' attribute of 'data' to get the data values in Volts, i.e, data in Volts = data * data.conversion * channel_conversion. This approach allows for both global and per-channel data conversion factors needed to support the storage of electrical recordings as native values generated by data acquisition systems. If this dataset is not present, then there is no channel-specific conversion factor, i.e. it is 1 for all channels.""")
     description: Optional[str] = Field(None, description="""Description of the time series.""")
     comments: Optional[str] = Field(None, description="""Human-readable comments about the TimeSeries. This second descriptive field can be used to store additional information, or descriptive information if the primary description field is populated with a computer-readable string.""")
     starting_time: Optional[TimeSeriesStartingTime] = Field(None, description="""Timestamp of the first sample in seconds. When timestamps are uniformly spaced, the timestamp of the first sample can be specified and all subsequent ones calculated from the sampling rate attribute.""")
-    control: Optional[TimeSeriesControl] = Field(None, description="""Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data.""")
-    control_description: Optional[TimeSeriesControlDescription] = Field(None, description="""Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0.""")
+    control: Optional[List[int]] = Field(default_factory=list, description="""Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data.""")
+    control_description: Optional[List[str]] = Field(default_factory=list, description="""Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0.""")
     sync: Optional[TimeSeriesSync] = Field(None, description="""Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of 'sync' are mostly for archival purposes.""")
     
 
@@ -91,9 +80,10 @@ class FeatureExtraction(NWBDataInterface):
     """
     Features, such as PC1 and PC2, that are extracted from signals stored in a SpikeEventSeries or other source.
     """
-    description: FeatureExtractionDescription = Field(..., description="""Description of features (eg, ''PC1'') for each of the extracted features.""")
+    name: str = Field(...)
+    description: List[str] = Field(default_factory=list, description="""Description of features (eg, ''PC1'') for each of the extracted features.""")
     features: FeatureExtractionFeatures = Field(..., description="""Multi-dimensional array of features extracted from each event.""")
-    times: FeatureExtractionTimes = Field(..., description="""Times of events that features correspond to (can be a link).""")
+    times: List[float] = Field(default_factory=list, description="""Times of events that features correspond to (can be a link).""")
     electrodes: FeatureExtractionElectrodes = Field(..., description="""DynamicTableRegion pointer to the electrodes that this time series was generated from.""")
     
 
@@ -101,36 +91,41 @@ class EventDetection(NWBDataInterface):
     """
     Detected spike events from voltage trace(s).
     """
+    name: str = Field(...)
     detection_method: str = Field(..., description="""Description of how events were detected, such as voltage threshold, or dV/dT threshold, as well as relevant values.""")
-    source_idx: EventDetectionSourceIdx = Field(..., description="""Indices (zero-based) into source ElectricalSeries::data array corresponding to time of event. ''description'' should define what is meant by time of event (e.g., .25 ms before action potential peak, zero-crossing time, etc). The index points to each event from the raw data.""")
-    times: EventDetectionTimes = Field(..., description="""Timestamps of events, in seconds.""")
+    source_idx: List[int] = Field(default_factory=list, description="""Indices (zero-based) into source ElectricalSeries::data array corresponding to time of event. ''description'' should define what is meant by time of event (e.g., .25 ms before action potential peak, zero-crossing time, etc). The index points to each event from the raw data.""")
+    times: List[float] = Field(default_factory=list, description="""Timestamps of events, in seconds.""")
     
 
 class EventWaveform(NWBDataInterface):
     """
     Represents either the waveforms of detected events, as extracted from a raw data trace in /acquisition, or the event waveforms that were stored during experiment acquisition.
     """
-    SpikeEventSeries: Optional[List[SpikeEventSeries]] = Field(default_factory=list, description="""SpikeEventSeries object(s) containing detected spike event waveforms.""")
+    name: str = Field(...)
+    spike_event_series: Optional[List[SpikeEventSeries]] = Field(default_factory=list, description="""SpikeEventSeries object(s) containing detected spike event waveforms.""")
     
 
 class FilteredEphys(NWBDataInterface):
     """
     Electrophysiology data from one or more channels that has been subjected to filtering. Examples of filtered data include Theta and Gamma (LFP has its own interface). FilteredEphys modules publish an ElectricalSeries for each filtered channel or set of channels. The name of each ElectricalSeries is arbitrary but should be informative. The source of the filtered data, whether this is from analysis of another time series or as acquired by hardware, should be noted in each's TimeSeries::description field. There is no assumed 1::1 correspondence between filtered ephys signals and electrodes, as a single signal can apply to many nearby electrodes, and one electrode may have different filtered (e.g., theta and/or gamma) signals represented. Filter properties should be noted in the ElectricalSeries 'filtering' attribute.
     """
-    ElectricalSeries: List[ElectricalSeries] = Field(default_factory=list, description="""ElectricalSeries object(s) containing filtered electrophysiology data.""")
+    name: str = Field(...)
+    electrical_series: List[ElectricalSeries] = Field(default_factory=list, description="""ElectricalSeries object(s) containing filtered electrophysiology data.""")
     
 
 class LFP(NWBDataInterface):
     """
     LFP data from one or more channels. The electrode map in each published ElectricalSeries will identify which channels are providing LFP data. Filter properties should be noted in the ElectricalSeries 'filtering' attribute.
     """
-    ElectricalSeries: List[ElectricalSeries] = Field(default_factory=list, description="""ElectricalSeries object(s) containing LFP data for one or more channels.""")
+    name: str = Field(...)
+    electrical_series: List[ElectricalSeries] = Field(default_factory=list, description="""ElectricalSeries object(s) containing LFP data for one or more channels.""")
     
 
 class ElectrodeGroup(NWBContainer):
     """
     A physical grouping of electrodes, e.g. a shank of an array.
     """
+    name: str = Field(...)
     description: Optional[str] = Field(None, description="""Description of this electrode group.""")
     location: Optional[str] = Field(None, description="""Location of electrode group. Specify the area, layer, comments on estimation of area/layer, etc. Use standard atlas names for anatomical regions when possible.""")
     position: Optional[Any] = Field(None, description="""stereotaxic or common framework coordinates""")
@@ -140,6 +135,7 @@ class ClusterWaveforms(NWBDataInterface):
     """
     DEPRECATED The mean waveform shape, including standard deviation, of the different clusters. Ideally, the waveform analysis should be performed on data that is only high-pass filtered. This is a separate module because it is expected to require updating. For example, IMEC probes may require different storage requirements to store/display mean waveforms, requiring a new interface or an extension of this one.
     """
+    name: str = Field(...)
     waveform_filtering: str = Field(..., description="""Filtering applied to data before generating mean/sd""")
     waveform_mean: ClusterWaveformsWaveformMean = Field(..., description="""The mean waveform for each cluster, using the same indices for each wave as cluster numbers in the associated Clustering module (i.e, cluster 3 is in array slot [3]). Waveforms corresponding to gaps in cluster sequence should be empty (e.g., zero- filled)""")
     waveform_sd: ClusterWaveformsWaveformSd = Field(..., description="""Stdev of waveforms for each cluster, using the same indices as in mean""")
@@ -149,22 +145,24 @@ class Clustering(NWBDataInterface):
     """
     DEPRECATED Clustered spike data, whether from automatic clustering tools (e.g., klustakwik) or as a result of manual sorting.
     """
+    name: str = Field(...)
     description: str = Field(..., description="""Description of clusters or clustering, (e.g. cluster 0 is noise, clusters curated using Klusters, etc)""")
-    num: ClusteringNum = Field(..., description="""Cluster number of each event""")
-    peak_over_rms: ClusteringPeakOverRms = Field(..., description="""Maximum ratio of waveform peak to RMS on any channel in the cluster (provides a basic clustering metric).""")
-    times: ClusteringTimes = Field(..., description="""Times of clustered events, in seconds. This may be a link to times field in associated FeatureExtraction module.""")
+    num: List[int] = Field(default_factory=list, description="""Cluster number of each event""")
+    peak_over_rms: List[float] = Field(default_factory=list, description="""Maximum ratio of waveform peak to RMS on any channel in the cluster (provides a basic clustering metric).""")
+    times: List[float] = Field(default_factory=list, description="""Times of clustered events, in seconds. This may be a link to times field in associated FeatureExtraction module.""")
     
 
 
-# Update forward refs
-# see https://pydantic-docs.helpmanual.io/usage/postponed_annotations/
-ElectricalSeries.update_forward_refs()
-SpikeEventSeries.update_forward_refs()
-FeatureExtraction.update_forward_refs()
-EventDetection.update_forward_refs()
-EventWaveform.update_forward_refs()
-FilteredEphys.update_forward_refs()
-LFP.update_forward_refs()
-ElectrodeGroup.update_forward_refs()
-ClusterWaveforms.update_forward_refs()
-Clustering.update_forward_refs()
+# Model rebuild
+# see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
+ElectricalSeries.model_rebuild()
+SpikeEventSeries.model_rebuild()
+FeatureExtraction.model_rebuild()
+EventDetection.model_rebuild()
+EventWaveform.model_rebuild()
+FilteredEphys.model_rebuild()
+LFP.model_rebuild()
+ElectrodeGroup.model_rebuild()
+ClusterWaveforms.model_rebuild()
+Clustering.model_rebuild()
+    

nwb_linkml/models/core_nwb_ecephys_include.py

@@ -23,13 +23,9 @@ from .nwb_language import (
 metamodel_version = "None"
 version = "None"
 
-class WeakRefShimBaseModel(BaseModel):
-   __slots__ = '__weakref__'
-
-class ConfiguredBaseModel(WeakRefShimBaseModel,
+class ConfiguredBaseModel(BaseModel,
                 validate_assignment = True,
-                validate_all = True,
-                underscore_attrs_are_private = True,
+                validate_default = True,
                 extra = 'forbid',
                 arbitrary_types_allowed = True,
                 use_enum_values = True):
@@ -40,8 +36,13 @@ class ElectricalSeriesData(ConfiguredBaseModel):
     """
     Recorded voltage data.
     """
+    name: str = Field("data", const=True)
     unit: Optional[str] = Field(None, description="""Base unit of measurement for working with the data. This value is fixed to 'volts'. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion', followed by 'channel_conversion' (if present), and then add 'offset'.""")
-    array: Optional[NDArray[Shape["* num_times, * num_channels, * num_samples"], Number]] = Field(None)
+    array: Optional[Union[
+        NDArray[Shape["* num_times"], Number],
+        NDArray[Shape["* num_times, * num_channels"], Number],
+        NDArray[Shape["* num_times, * num_channels, * num_samples"], Number]
+    ]] = Field(None)
     
 
 class ElectricalSeriesDataArray(Arraylike):
@@ -55,25 +56,27 @@ class ElectricalSeriesElectrodes(DynamicTableRegion):
     """
     DynamicTableRegion pointer to the electrodes that this time series was generated from.
     """
+    name: str = Field("electrodes", const=True)
     table: Optional[DynamicTable] = Field(None, description="""Reference to the DynamicTable object that this region applies to.""")
     description: Optional[str] = Field(None, description="""Description of what this table region points to.""")
-    array: Optional[NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], ]] = Field(None)
-    
-
-class ElectricalSeriesChannelConversion(ConfiguredBaseModel):
-    """
-    Channel-specific conversion factor. Multiply the data in the 'data' dataset by these values along the channel axis (as indicated by axis attribute) AND by the global conversion factor in the 'conversion' attribute of 'data' to get the data values in Volts, i.e, data in Volts = data * data.conversion * channel_conversion. This approach allows for both global and per-channel data conversion factors needed to support the storage of electrical recordings as native values generated by data acquisition systems. If this dataset is not present, then there is no channel-specific conversion factor, i.e. it is 1 for all channels.
-    """
-    axis: Optional[int] = Field(None, description="""The zero-indexed axis of the 'data' dataset that the channel-specific conversion factor corresponds to. This value is fixed to 1.""")
-    channel_conversion: Optional[List[float]] = Field(default_factory=list, description="""Channel-specific conversion factor. Multiply the data in the 'data' dataset by these values along the channel axis (as indicated by axis attribute) AND by the global conversion factor in the 'conversion' attribute of 'data' to get the data values in Volts, i.e, data in Volts = data * data.conversion * channel_conversion. This approach allows for both global and per-channel data conversion factors needed to support the storage of electrical recordings as native values generated by data acquisition systems. If this dataset is not present, then there is no channel-specific conversion factor, i.e. it is 1 for all channels.""")
+    array: Optional[Union[
+        NDArray[Shape["* dim0"], Any],
+        NDArray[Shape["* dim0, * dim1"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], Any]
+    ]] = Field(None)
     
 
 class SpikeEventSeriesData(ConfiguredBaseModel):
     """
     Spike waveforms.
     """
+    name: str = Field("data", const=True)
     unit: Optional[str] = Field(None, description="""Unit of measurement for waveforms, which is fixed to 'volts'.""")
-    array: Optional[NDArray[Shape["* num_events, * num_samples, * num_channels"], Number]] = Field(None)
+    array: Optional[Union[
+        NDArray[Shape["* num_events, * num_samples"], Number],
+        NDArray[Shape["* num_events, * num_samples, * num_channels"], Number]
+    ]] = Field(None)
     
 
 class SpikeEventSeriesDataArray(Arraylike):
@@ -83,135 +86,77 @@ class SpikeEventSeriesDataArray(Arraylike):
     num_channels: Optional[float] = Field(None)
     
 
-class SpikeEventSeriesTimestamps(ConfiguredBaseModel):
-    """
-    Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time. Timestamps are required for the events. Unlike for TimeSeries, timestamps are required for SpikeEventSeries and are thus re-specified here.
-    """
-    interval: Optional[int] = Field(None, description="""Value is '1'""")
-    unit: Optional[str] = Field(None, description="""Unit of measurement for timestamps, which is fixed to 'seconds'.""")
-    timestamps: List[float] = Field(default_factory=list, description="""Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time. Timestamps are required for the events. Unlike for TimeSeries, timestamps are required for SpikeEventSeries and are thus re-specified here.""")
-    
-
-class FeatureExtractionDescription(ConfiguredBaseModel):
-    """
-    Description of features (eg, ''PC1'') for each of the extracted features.
-    """
-    description: List[str] = Field(default_factory=list, description="""Description of features (eg, ''PC1'') for each of the extracted features.""")
-    
-
 class FeatureExtractionFeatures(ConfiguredBaseModel):
     """
     Multi-dimensional array of features extracted from each event.
     """
+    name: str = Field("features", const=True)
     array: Optional[NDArray[Shape["* num_events, * num_channels, * num_features"], Float32]] = Field(None)
     
 
 class FeatureExtractionFeaturesArray(Arraylike):
     
-    num_events: Optional[float] = Field(None)
-    num_channels: Optional[float] = Field(None)
-    num_features: Optional[float] = Field(None)
-    
-
-class FeatureExtractionTimes(ConfiguredBaseModel):
-    """
-    Times of events that features correspond to (can be a link).
-    """
-    times: List[float] = Field(default_factory=list, description="""Times of events that features correspond to (can be a link).""")
+    num_events: float = Field(...)
+    num_channels: float = Field(...)
+    num_features: float = Field(...)
     
 
 class FeatureExtractionElectrodes(DynamicTableRegion):
     """
     DynamicTableRegion pointer to the electrodes that this time series was generated from.
     """
+    name: str = Field("electrodes", const=True)
     table: Optional[DynamicTable] = Field(None, description="""Reference to the DynamicTable object that this region applies to.""")
     description: Optional[str] = Field(None, description="""Description of what this table region points to.""")
-    array: Optional[NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], ]] = Field(None)
-    
-
-class EventDetectionSourceIdx(ConfiguredBaseModel):
-    """
-    Indices (zero-based) into source ElectricalSeries::data array corresponding to time of event. ''description'' should define what is meant by time of event (e.g., .25 ms before action potential peak, zero-crossing time, etc). The index points to each event from the raw data.
-    """
-    source_idx: List[int] = Field(default_factory=list, description="""Indices (zero-based) into source ElectricalSeries::data array corresponding to time of event. ''description'' should define what is meant by time of event (e.g., .25 ms before action potential peak, zero-crossing time, etc). The index points to each event from the raw data.""")
-    
-
-class EventDetectionTimes(ConfiguredBaseModel):
-    """
-    Timestamps of events, in seconds.
-    """
-    unit: Optional[str] = Field(None, description="""Unit of measurement for event times, which is fixed to 'seconds'.""")
-    times: List[float] = Field(default_factory=list, description="""Timestamps of events, in seconds.""")
+    array: Optional[Union[
+        NDArray[Shape["* dim0"], Any],
+        NDArray[Shape["* dim0, * dim1"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], Any]
+    ]] = Field(None)
     
 
 class ClusterWaveformsWaveformMean(ConfiguredBaseModel):
     """
     The mean waveform for each cluster, using the same indices for each wave as cluster numbers in the associated Clustering module (i.e, cluster 3 is in array slot [3]). Waveforms corresponding to gaps in cluster sequence should be empty (e.g., zero- filled)
     """
+    name: str = Field("waveform_mean", const=True)
     array: Optional[NDArray[Shape["* num_clusters, * num_samples"], Float32]] = Field(None)
     
 
 class ClusterWaveformsWaveformMeanArray(Arraylike):
     
-    num_clusters: Optional[float] = Field(None)
-    num_samples: Optional[float] = Field(None)
+    num_clusters: float = Field(...)
+    num_samples: float = Field(...)
     
 
 class ClusterWaveformsWaveformSd(ConfiguredBaseModel):
     """
     Stdev of waveforms for each cluster, using the same indices as in mean
     """
+    name: str = Field("waveform_sd", const=True)
     array: Optional[NDArray[Shape["* num_clusters, * num_samples"], Float32]] = Field(None)
     
 
 class ClusterWaveformsWaveformSdArray(Arraylike):
     
-    num_clusters: Optional[float] = Field(None)
-    num_samples: Optional[float] = Field(None)
-    
-
-class ClusteringNum(ConfiguredBaseModel):
-    """
-    Cluster number of each event
-    """
-    num: List[int] = Field(default_factory=list, description="""Cluster number of each event""")
-    
-
-class ClusteringPeakOverRms(ConfiguredBaseModel):
-    """
-    Maximum ratio of waveform peak to RMS on any channel in the cluster (provides a basic clustering metric).
-    """
-    peak_over_rms: List[float] = Field(default_factory=list, description="""Maximum ratio of waveform peak to RMS on any channel in the cluster (provides a basic clustering metric).""")
-    
-
-class ClusteringTimes(ConfiguredBaseModel):
-    """
-    Times of clustered events, in seconds. This may be a link to times field in associated FeatureExtraction module.
-    """
-    times: List[float] = Field(default_factory=list, description="""Times of clustered events, in seconds. This may be a link to times field in associated FeatureExtraction module.""")
+    num_clusters: float = Field(...)
+    num_samples: float = Field(...)
     
 
 
-# Update forward refs
-# see https://pydantic-docs.helpmanual.io/usage/postponed_annotations/
-ElectricalSeriesData.update_forward_refs()
-ElectricalSeriesDataArray.update_forward_refs()
-ElectricalSeriesElectrodes.update_forward_refs()
-ElectricalSeriesChannelConversion.update_forward_refs()
-SpikeEventSeriesData.update_forward_refs()
-SpikeEventSeriesDataArray.update_forward_refs()
-SpikeEventSeriesTimestamps.update_forward_refs()
-FeatureExtractionDescription.update_forward_refs()
-FeatureExtractionFeatures.update_forward_refs()
-FeatureExtractionFeaturesArray.update_forward_refs()
-FeatureExtractionTimes.update_forward_refs()
-FeatureExtractionElectrodes.update_forward_refs()
-EventDetectionSourceIdx.update_forward_refs()
-EventDetectionTimes.update_forward_refs()
-ClusterWaveformsWaveformMean.update_forward_refs()
-ClusterWaveformsWaveformMeanArray.update_forward_refs()
-ClusterWaveformsWaveformSd.update_forward_refs()
-ClusterWaveformsWaveformSdArray.update_forward_refs()
-ClusteringNum.update_forward_refs()
-ClusteringPeakOverRms.update_forward_refs()
-ClusteringTimes.update_forward_refs()
+# Model rebuild
+# see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
+ElectricalSeriesData.model_rebuild()
+ElectricalSeriesDataArray.model_rebuild()
+ElectricalSeriesElectrodes.model_rebuild()
+SpikeEventSeriesData.model_rebuild()
+SpikeEventSeriesDataArray.model_rebuild()
+FeatureExtractionFeatures.model_rebuild()
+FeatureExtractionFeaturesArray.model_rebuild()
+FeatureExtractionElectrodes.model_rebuild()
+ClusterWaveformsWaveformMean.model_rebuild()
+ClusterWaveformsWaveformMeanArray.model_rebuild()
+ClusterWaveformsWaveformSd.model_rebuild()
+ClusterWaveformsWaveformSdArray.model_rebuild()
+    

nwb_linkml/models/core_nwb_epoch.py

@@ -11,27 +11,23 @@ else:
     from typing_extensions import Literal
 
 
-from .core_nwb_epoch_include import (
-    TimeIntervalsTimeseriesIndex,
-    TimeIntervalsTagsIndex,
-    TimeIntervalsTimeseries
-)
-
 from .hdmf_common_table import (
     DynamicTable
 )
 
+from .core_nwb_epoch_include import (
+    TimeIntervalsTimeseriesIndex,
+    TimeIntervalsTimeseries,
+    TimeIntervalsTagsIndex
+)
+
 
 metamodel_version = "None"
 version = "None"
 
-class WeakRefShimBaseModel(BaseModel):
-   __slots__ = '__weakref__'
-
-class ConfiguredBaseModel(WeakRefShimBaseModel,
+class ConfiguredBaseModel(BaseModel,
                 validate_assignment = True,
-                validate_all = True,
-                underscore_attrs_are_private = True,
+                validate_default = True,
                 extra = 'forbid',
                 arbitrary_types_allowed = True,
                 use_enum_values = True):
@@ -42,6 +38,7 @@ class TimeIntervals(DynamicTable):
     """
     A container for aggregating epoch data and the TimeSeries that each epoch applies to.
     """
+    name: str = Field(...)
     start_time: Optional[List[float]] = Field(default_factory=list, description="""Start time of epoch, in seconds.""")
     stop_time: Optional[List[float]] = Field(default_factory=list, description="""Stop time of epoch, in seconds.""")
     tags: Optional[List[str]] = Field(default_factory=list, description="""User-defined tags that identify or categorize events.""")
@@ -50,11 +47,12 @@ class TimeIntervals(DynamicTable):
     timeseries_index: Optional[TimeIntervalsTimeseriesIndex] = Field(None, description="""Index for timeseries.""")
     colnames: Optional[str] = Field(None, description="""The names of the columns in this table. This should be used to specify an order to the columns.""")
     description: Optional[str] = Field(None, description="""Description of what is in this dynamic table.""")
-    id: DynamicTableId = Field(..., description="""Array of unique identifiers for the rows of this dynamic table.""")
+    id: List[int] = Field(default_factory=list, description="""Array of unique identifiers for the rows of this dynamic table.""")
     VectorData: Optional[List[VectorData]] = Field(default_factory=list, description="""Vector columns, including index columns, of this dynamic table.""")
     
 
 
-# Update forward refs
-# see https://pydantic-docs.helpmanual.io/usage/postponed_annotations/
-TimeIntervals.update_forward_refs()
+# Model rebuild
+# see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
+TimeIntervals.model_rebuild()
+    

nwb_linkml/models/core_nwb_epoch_include.py

@@ -11,25 +11,21 @@ else:
     from typing_extensions import Literal
 
 
-from .core_nwb_base import (
-    TimeSeriesReferenceVectorData
-)
-
 from .hdmf_common_table import (
     VectorIndex
 )
 
+from .core_nwb_base import (
+    TimeSeriesReferenceVectorData
+)
+
 
 metamodel_version = "None"
 version = "None"
 
-class WeakRefShimBaseModel(BaseModel):
-   __slots__ = '__weakref__'
-
-class ConfiguredBaseModel(WeakRefShimBaseModel,
+class ConfiguredBaseModel(BaseModel,
                 validate_assignment = True,
-                validate_all = True,
-                underscore_attrs_are_private = True,
+                validate_default = True,
                 extra = 'forbid',
                 arbitrary_types_allowed = True,
                 use_enum_values = True):
@@ -40,31 +36,50 @@ class TimeIntervalsTagsIndex(VectorIndex):
     """
     Index for tags.
     """
+    name: str = Field("tags_index", const=True)
     target: Optional[VectorData] = Field(None, description="""Reference to the target dataset that this index applies to.""")
     description: Optional[str] = Field(None, description="""Description of what these vectors represent.""")
-    array: Optional[NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], ]] = Field(None)
+    array: Optional[Union[
+        NDArray[Shape["* dim0"], Any],
+        NDArray[Shape["* dim0, * dim1"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], Any]
+    ]] = Field(None)
     
 
 class TimeIntervalsTimeseries(TimeSeriesReferenceVectorData):
     """
     An index into a TimeSeries object.
     """
+    name: str = Field("timeseries", const=True)
     description: Optional[str] = Field(None, description="""Description of what these vectors represent.""")
-    array: Optional[NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], ]] = Field(None)
+    array: Optional[Union[
+        NDArray[Shape["* dim0"], Any],
+        NDArray[Shape["* dim0, * dim1"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], Any]
+    ]] = Field(None)
     
 
 class TimeIntervalsTimeseriesIndex(VectorIndex):
     """
     Index for timeseries.
     """
+    name: str = Field("timeseries_index", const=True)
     target: Optional[VectorData] = Field(None, description="""Reference to the target dataset that this index applies to.""")
     description: Optional[str] = Field(None, description="""Description of what these vectors represent.""")
-    array: Optional[NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], ]] = Field(None)
+    array: Optional[Union[
+        NDArray[Shape["* dim0"], Any],
+        NDArray[Shape["* dim0, * dim1"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], Any]
+    ]] = Field(None)
     
 
 
-# Update forward refs
-# see https://pydantic-docs.helpmanual.io/usage/postponed_annotations/
-TimeIntervalsTagsIndex.update_forward_refs()
-TimeIntervalsTimeseries.update_forward_refs()
-TimeIntervalsTimeseriesIndex.update_forward_refs()
+# Model rebuild
+# see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
+TimeIntervalsTagsIndex.model_rebuild()
+TimeIntervalsTimeseries.model_rebuild()
+TimeIntervalsTimeseriesIndex.model_rebuild()
+    

nwb_linkml/models/core_nwb_file.py

@@ -11,35 +11,35 @@ else:
     from typing_extensions import Literal
 
 
-from .core_nwb_file_include import (
-    NWBFileScratch,
-    NWBFileGeneral,
-    NWBFileIntervals,
-    NWBFileFileCreateDate,
-    NWBFileUnits,
-    SubjectAge,
-    NWBFileStimulus,
-    NWBFileAcquisition,
-    NWBFileProcessing,
-    NWBFileAnalysis
+from .hdmf_common_table import (
+    DynamicTable
 )
 
 from .core_nwb_base import (
-    NWBContainer,
-    NWBData
+    NWBData,
+    ProcessingModule,
+    NWBDataInterface,
+    NWBContainer
+)
+
+from .core_nwb_file_include import (
+    NWBFileGeneral,
+    SubjectAge,
+    NWBFileIntervals,
+    NWBFileStimulus
+)
+
+from .core_nwb_misc import (
+    Units
 )
 
 
 metamodel_version = "None"
 version = "None"
 
-class WeakRefShimBaseModel(BaseModel):
-   __slots__ = '__weakref__'
-
-class ConfiguredBaseModel(WeakRefShimBaseModel,
+class ConfiguredBaseModel(BaseModel,
                 validate_assignment = True,
-                validate_all = True,
-                underscore_attrs_are_private = True,
+                validate_default = True,
                 extra = 'forbid',
                 arbitrary_types_allowed = True,
                 use_enum_values = True):
@@ -50,6 +50,7 @@ class ScratchData(NWBData):
     """
     Any one-off datasets
     """
+    name: str = Field(...)
     notes: Optional[str] = Field(None, description="""Any notes the user has about the dataset being stored""")
     
 
@@ -57,35 +58,37 @@ class NWBFile(NWBContainer):
     """
     An NWB file storing cellular-based neurophysiology data from a single experimental session.
     """
+    name: str = Field("root", const=True)
     nwb_version: Optional[str] = Field(None, description="""File version string. Use semantic versioning, e.g. 1.2.1. This will be the name of the format with trailing major, minor and patch numbers.""")
-    file_create_date: NWBFileFileCreateDate = Field(..., description="""A record of the date the file was created and of subsequent modifications. The date is stored in UTC with local timezone offset as ISO 8601 extended formatted strings: 2018-09-28T14:43:54.123+02:00. Dates stored in UTC end in \"Z\" with no timezone offset. Date accuracy is up to milliseconds. The file can be created after the experiment was run, so this may differ from the experiment start time. Each modification to the nwb file adds a new entry to the array.""")
+    file_create_date: List[datetime ] = Field(default_factory=list, description="""A record of the date the file was created and of subsequent modifications. The date is stored in UTC with local timezone offset as ISO 8601 extended formatted strings: 2018-09-28T14:43:54.123+02:00. Dates stored in UTC end in \"Z\" with no timezone offset. Date accuracy is up to milliseconds. The file can be created after the experiment was run, so this may differ from the experiment start time. Each modification to the nwb file adds a new entry to the array.""")
     identifier: str = Field(..., description="""A unique text identifier for the file. For example, concatenated lab name, file creation date/time and experimentalist, or a hash of these and/or other values. The goal is that the string should be unique to all other files.""")
     session_description: str = Field(..., description="""A description of the experimental session and data in the file.""")
-    session_start_time: date = Field(..., description="""Date and time of the experiment/session start. The date is stored in UTC with local timezone offset as ISO 8601 extended formatted string: 2018-09-28T14:43:54.123+02:00. Dates stored in UTC end in \"Z\" with no timezone offset. Date accuracy is up to milliseconds.""")
-    timestamps_reference_time: date = Field(..., description="""Date and time corresponding to time zero of all timestamps. The date is stored in UTC with local timezone offset as ISO 8601 extended formatted string: 2018-09-28T14:43:54.123+02:00. Dates stored in UTC end in \"Z\" with no timezone offset. Date accuracy is up to milliseconds. All times stored in the file use this time as reference (i.e., time zero).""")
-    acquisition: NWBFileAcquisition = Field(..., description="""Data streams recorded from the system, including ephys, ophys, tracking, etc. This group should be read-only after the experiment is completed and timestamps are corrected to a common timebase. The data stored here may be links to raw data stored in external NWB files. This will allow keeping bulky raw data out of the file while preserving the option of keeping some/all in the file. Acquired data includes tracking and experimental data streams (i.e., everything measured from the system). If bulky data is stored in the /acquisition group, the data can exist in a separate NWB file that is linked to by the file being used for processing and analysis.""")
-    analysis: NWBFileAnalysis = Field(..., description="""Lab-specific and custom scientific analysis of data. There is no defined format for the content of this group - the format is up to the individual user/lab. To facilitate sharing analysis data between labs, the contents here should be stored in standard types (e.g., neurodata_types) and appropriately documented. The file can store lab-specific and custom data analysis without restriction on its form or schema, reducing data formatting restrictions on end users. Such data should be placed in the analysis group. The analysis data should be documented so that it could be shared with other labs.""")
-    scratch: Optional[NWBFileScratch] = Field(None, description="""A place to store one-off analysis results. Data placed here is not intended for sharing. By placing data here, users acknowledge that there is no guarantee that their data meets any standard.""")
-    processing: NWBFileProcessing = Field(..., description="""The home for ProcessingModules. These modules perform intermediate analysis of data that is necessary to perform before scientific analysis. Examples include spike clustering, extracting position from tracking data, stitching together image slices. ProcessingModules can be large and express many data sets from relatively complex analysis (e.g., spike detection and clustering) or small, representing extraction of position information from tracking video, or even binary lick/no-lick decisions. Common software tools (e.g., klustakwik, MClust) are expected to read/write data here.  'Processing' refers to intermediate analysis of the acquired data to make it more amenable to scientific analysis.""")
+    session_start_time: datetime  = Field(..., description="""Date and time of the experiment/session start. The date is stored in UTC with local timezone offset as ISO 8601 extended formatted string: 2018-09-28T14:43:54.123+02:00. Dates stored in UTC end in \"Z\" with no timezone offset. Date accuracy is up to milliseconds.""")
+    timestamps_reference_time: datetime  = Field(..., description="""Date and time corresponding to time zero of all timestamps. The date is stored in UTC with local timezone offset as ISO 8601 extended formatted string: 2018-09-28T14:43:54.123+02:00. Dates stored in UTC end in \"Z\" with no timezone offset. Date accuracy is up to milliseconds. All times stored in the file use this time as reference (i.e., time zero).""")
+    acquisition: Optional[List[Union[DynamicTable, NWBDataInterface]]] = Field(default_factory=list, description="""Data streams recorded from the system, including ephys, ophys, tracking, etc. This group should be read-only after the experiment is completed and timestamps are corrected to a common timebase. The data stored here may be links to raw data stored in external NWB files. This will allow keeping bulky raw data out of the file while preserving the option of keeping some/all in the file. Acquired data includes tracking and experimental data streams (i.e., everything measured from the system). If bulky data is stored in the /acquisition group, the data can exist in a separate NWB file that is linked to by the file being used for processing and analysis.""")
+    analysis: Optional[List[Union[DynamicTable, NWBContainer]]] = Field(default_factory=list, description="""Lab-specific and custom scientific analysis of data. There is no defined format for the content of this group - the format is up to the individual user/lab. To facilitate sharing analysis data between labs, the contents here should be stored in standard types (e.g., neurodata_types) and appropriately documented. The file can store lab-specific and custom data analysis without restriction on its form or schema, reducing data formatting restrictions on end users. Such data should be placed in the analysis group. The analysis data should be documented so that it could be shared with other labs.""")
+    scratch: Optional[List[Union[DynamicTable, NWBContainer]]] = Field(default_factory=list, description="""A place to store one-off analysis results. Data placed here is not intended for sharing. By placing data here, users acknowledge that there is no guarantee that their data meets any standard.""")
+    processing: Optional[List[ProcessingModule]] = Field(default_factory=list, description="""The home for ProcessingModules. These modules perform intermediate analysis of data that is necessary to perform before scientific analysis. Examples include spike clustering, extracting position from tracking data, stitching together image slices. ProcessingModules can be large and express many data sets from relatively complex analysis (e.g., spike detection and clustering) or small, representing extraction of position information from tracking video, or even binary lick/no-lick decisions. Common software tools (e.g., klustakwik, MClust) are expected to read/write data here.  'Processing' refers to intermediate analysis of the acquired data to make it more amenable to scientific analysis.""")
     stimulus: NWBFileStimulus = Field(..., description="""Data pushed into the system (eg, video stimulus, sound, voltage, etc) and secondary representations of that data (eg, measurements of something used as a stimulus). This group should be made read-only after experiment complete and timestamps are corrected to common timebase. Stores both presented stimuli and stimulus templates, the latter in case the same stimulus is presented multiple times, or is pulled from an external stimulus library. Stimuli are here defined as any signal that is pushed into the system as part of the experiment (eg, sound, video, voltage, etc). Many different experiments can use the same stimuli, and stimuli can be re-used during an experiment. The stimulus group is organized so that one version of template stimuli can be stored and these be used multiple times. These templates can exist in the present file or can be linked to a remote library file.""")
     general: NWBFileGeneral = Field(..., description="""Experimental metadata, including protocol, notes and description of hardware device(s).  The metadata stored in this section should be used to describe the experiment. Metadata necessary for interpreting the data is stored with the data. General experimental metadata, including animal strain, experimental protocols, experimenter, devices, etc, are stored under 'general'. Core metadata (e.g., that required to interpret data fields) is stored with the data itself, and implicitly defined by the file specification (e.g., time is in seconds). The strategy used here for storing non-core metadata is to use free-form text fields, such as would appear in sentences or paragraphs from a Methods section. Metadata fields are text to enable them to be more general, for example to represent ranges instead of numerical values. Machine-readable metadata is stored as attributes to these free-form datasets. All entries in the below table are to be included when data is present. Unused groups (e.g., intracellular_ephys in an optophysiology experiment) should not be created unless there is data to store within them.""")
     intervals: Optional[NWBFileIntervals] = Field(None, description="""Experimental intervals, whether that be logically distinct sub-experiments having a particular scientific goal, trials (see trials subgroup) during an experiment, or epochs (see epochs subgroup) deriving from analysis of data.""")
-    units: Optional[NWBFileUnits] = Field(None, description="""Data about sorted spike units.""")
+    units: Optional[Units] = Field(None, description="""Data about sorted spike units.""")
     
 
 class LabMetaData(NWBContainer):
     """
     Lab-specific meta-data.
     """
-    None
+    name: str = Field(...)
     
 
 class Subject(NWBContainer):
     """
     Information about the animal or person from which the data was measured.
     """
+    name: str = Field(...)
     age: Optional[SubjectAge] = Field(None, description="""Age of subject. Can be supplied instead of 'date_of_birth'.""")
-    date_of_birth: Optional[date] = Field(None, description="""Date of birth of subject. Can be supplied instead of 'age'.""")
+    date_of_birth: Optional[datetime ] = Field(None, description="""Date of birth of subject. Can be supplied instead of 'age'.""")
     description: Optional[str] = Field(None, description="""Description of subject and where subject came from (e.g., breeder, if animal).""")
     genotype: Optional[str] = Field(None, description="""Genetic strain. If absent, assume Wild Type (WT).""")
     sex: Optional[str] = Field(None, description="""Gender of subject.""")
@@ -96,9 +99,10 @@ class Subject(NWBContainer):
     
 
 
-# Update forward refs
-# see https://pydantic-docs.helpmanual.io/usage/postponed_annotations/
-ScratchData.update_forward_refs()
-NWBFile.update_forward_refs()
-LabMetaData.update_forward_refs()
-Subject.update_forward_refs()
+# Model rebuild
+# see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
+ScratchData.model_rebuild()
+NWBFile.model_rebuild()
+LabMetaData.model_rebuild()
+Subject.model_rebuild()
+    

nwb_linkml/models/core_nwb_file_include.py

@@ -11,40 +11,36 @@ else:
     from typing_extensions import Literal
 
 
-from .core_nwb_file import (
-    LabMetaData,
-    ScratchData,
-    Subject
-)
-
-from .core_nwb_misc import (
-    Units
-)
-
 from .core_nwb_base import (
     TimeSeries,
-    Images,
-    NWBContainer,
-    NWBDataInterface,
-    ProcessingModule
+    Images
 )
 
 from .core_nwb_icephys import (
-    RepetitionsTable,
     ExperimentalConditionsTable,
-    IntracellularElectrode,
-    SimultaneousRecordingsTable,
     SweepTable,
+    IntracellularElectrode,
     SequentialRecordingsTable,
+    RepetitionsTable,
+    SimultaneousRecordingsTable,
     IntracellularRecordingsTable
 )
 
+from .core_nwb_ogen import (
+    OptogeneticStimulusSite
+)
+
 from .core_nwb_epoch import (
     TimeIntervals
 )
 
-from .core_nwb_ogen import (
-    OptogeneticStimulusSite
+from .core_nwb_file import (
+    LabMetaData,
+    Subject
+)
+
+from .hdmf_common_table import (
+    DynamicTable
 )
 
 from .core_nwb_device import (
@@ -55,10 +51,6 @@ from .core_nwb_ecephys import (
     ElectrodeGroup
 )
 
-from .hdmf_common_table import (
-    DynamicTable
-)
-
 from .core_nwb_ophys import (
     ImagingPlane
 )
@@ -67,414 +59,113 @@ from .core_nwb_ophys import (
 metamodel_version = "None"
 version = "None"
 
-class WeakRefShimBaseModel(BaseModel):
-   __slots__ = '__weakref__'
-
-class ConfiguredBaseModel(WeakRefShimBaseModel,
+class ConfiguredBaseModel(BaseModel,
                 validate_assignment = True,
-                validate_all = True,
-                underscore_attrs_are_private = True,
+                validate_default = True,
                 extra = 'forbid',
                 arbitrary_types_allowed = True,
                 use_enum_values = True):
     pass
 
 
-class NWBFileFileCreateDate(ConfiguredBaseModel):
-    """
-    A record of the date the file was created and of subsequent modifications. The date is stored in UTC with local timezone offset as ISO 8601 extended formatted strings: 2018-09-28T14:43:54.123+02:00. Dates stored in UTC end in \"Z\" with no timezone offset. Date accuracy is up to milliseconds. The file can be created after the experiment was run, so this may differ from the experiment start time. Each modification to the nwb file adds a new entry to the array.
-    """
-    file_create_date: List[date] = Field(default_factory=list, description="""A record of the date the file was created and of subsequent modifications. The date is stored in UTC with local timezone offset as ISO 8601 extended formatted strings: 2018-09-28T14:43:54.123+02:00. Dates stored in UTC end in \"Z\" with no timezone offset. Date accuracy is up to milliseconds. The file can be created after the experiment was run, so this may differ from the experiment start time. Each modification to the nwb file adds a new entry to the array.""")
-    
-
-class NWBFileAcquisition(ConfiguredBaseModel):
-    """
-    Data streams recorded from the system, including ephys, ophys, tracking, etc. This group should be read-only after the experiment is completed and timestamps are corrected to a common timebase. The data stored here may be links to raw data stored in external NWB files. This will allow keeping bulky raw data out of the file while preserving the option of keeping some/all in the file. Acquired data includes tracking and experimental data streams (i.e., everything measured from the system). If bulky data is stored in the /acquisition group, the data can exist in a separate NWB file that is linked to by the file being used for processing and analysis.
-    """
-    NWBDataInterface: Optional[List[NWBDataInterface]] = Field(default_factory=list, description="""Acquired, raw data.""")
-    DynamicTable: Optional[List[DynamicTable]] = Field(default_factory=list, description="""Tabular data that is relevant to acquisition""")
-    
-
-class NWBFileAnalysis(ConfiguredBaseModel):
-    """
-    Lab-specific and custom scientific analysis of data. There is no defined format for the content of this group - the format is up to the individual user/lab. To facilitate sharing analysis data between labs, the contents here should be stored in standard types (e.g., neurodata_types) and appropriately documented. The file can store lab-specific and custom data analysis without restriction on its form or schema, reducing data formatting restrictions on end users. Such data should be placed in the analysis group. The analysis data should be documented so that it could be shared with other labs.
-    """
-    NWBContainer: Optional[List[NWBContainer]] = Field(default_factory=list, description="""Custom analysis results.""")
-    DynamicTable: Optional[List[DynamicTable]] = Field(default_factory=list, description="""Tabular data that is relevant to data stored in analysis""")
-    
-
-class NWBFileScratch(ConfiguredBaseModel):
-    """
-    A place to store one-off analysis results. Data placed here is not intended for sharing. By placing data here, users acknowledge that there is no guarantee that their data meets any standard.
-    """
-    ScratchData: Optional[List[ScratchData]] = Field(default_factory=list, description="""Any one-off datasets""")
-    NWBContainer: Optional[List[NWBContainer]] = Field(default_factory=list, description="""Any one-off containers""")
-    DynamicTable: Optional[List[DynamicTable]] = Field(default_factory=list, description="""Any one-off tables""")
-    
-
-class NWBFileProcessing(ConfiguredBaseModel):
-    """
-    The home for ProcessingModules. These modules perform intermediate analysis of data that is necessary to perform before scientific analysis. Examples include spike clustering, extracting position from tracking data, stitching together image slices. ProcessingModules can be large and express many data sets from relatively complex analysis (e.g., spike detection and clustering) or small, representing extraction of position information from tracking video, or even binary lick/no-lick decisions. Common software tools (e.g., klustakwik, MClust) are expected to read/write data here.  'Processing' refers to intermediate analysis of the acquired data to make it more amenable to scientific analysis.
-    """
-    ProcessingModule: Optional[List[ProcessingModule]] = Field(default_factory=list, description="""Intermediate analysis of acquired data.""")
-    
-
 class NWBFileStimulus(ConfiguredBaseModel):
     """
     Data pushed into the system (eg, video stimulus, sound, voltage, etc) and secondary representations of that data (eg, measurements of something used as a stimulus). This group should be made read-only after experiment complete and timestamps are corrected to common timebase. Stores both presented stimuli and stimulus templates, the latter in case the same stimulus is presented multiple times, or is pulled from an external stimulus library. Stimuli are here defined as any signal that is pushed into the system as part of the experiment (eg, sound, video, voltage, etc). Many different experiments can use the same stimuli, and stimuli can be re-used during an experiment. The stimulus group is organized so that one version of template stimuli can be stored and these be used multiple times. These templates can exist in the present file or can be linked to a remote library file.
     """
-    presentation: NWBFileStimulusPresentation = Field(..., description="""Stimuli presented during the experiment.""")
-    templates: NWBFileStimulusTemplates = Field(..., description="""Template stimuli. Timestamps in templates are based on stimulus design and are relative to the beginning of the stimulus. When templates are used, the stimulus instances must convert presentation times to the experiment`s time reference frame.""")
-    
-
-class NWBFileStimulusPresentation(ConfiguredBaseModel):
-    """
-    Stimuli presented during the experiment.
-    """
-    TimeSeries: Optional[List[TimeSeries]] = Field(default_factory=list, description="""TimeSeries objects containing data of presented stimuli.""")
-    
-
-class NWBFileStimulusTemplates(ConfiguredBaseModel):
-    """
-    Template stimuli. Timestamps in templates are based on stimulus design and are relative to the beginning of the stimulus. When templates are used, the stimulus instances must convert presentation times to the experiment`s time reference frame.
-    """
-    TimeSeries: Optional[List[TimeSeries]] = Field(default_factory=list, description="""TimeSeries objects containing template data of presented stimuli.""")
-    Images: Optional[List[Images]] = Field(default_factory=list, description="""Images objects containing images of presented stimuli.""")
+    name: str = Field("stimulus", const=True)
+    presentation: Optional[List[TimeSeries]] = Field(default_factory=list, description="""Stimuli presented during the experiment.""")
+    templates: Optional[List[Union[Images, TimeSeries]]] = Field(default_factory=list, description="""Template stimuli. Timestamps in templates are based on stimulus design and are relative to the beginning of the stimulus. When templates are used, the stimulus instances must convert presentation times to the experiment`s time reference frame.""")
     
 
 class NWBFileGeneral(ConfiguredBaseModel):
     """
     Experimental metadata, including protocol, notes and description of hardware device(s).  The metadata stored in this section should be used to describe the experiment. Metadata necessary for interpreting the data is stored with the data. General experimental metadata, including animal strain, experimental protocols, experimenter, devices, etc, are stored under 'general'. Core metadata (e.g., that required to interpret data fields) is stored with the data itself, and implicitly defined by the file specification (e.g., time is in seconds). The strategy used here for storing non-core metadata is to use free-form text fields, such as would appear in sentences or paragraphs from a Methods section. Metadata fields are text to enable them to be more general, for example to represent ranges instead of numerical values. Machine-readable metadata is stored as attributes to these free-form datasets. All entries in the below table are to be included when data is present. Unused groups (e.g., intracellular_ephys in an optophysiology experiment) should not be created unless there is data to store within them.
     """
+    name: str = Field("general", const=True)
     data_collection: Optional[str] = Field(None, description="""Notes about data collection and analysis.""")
     experiment_description: Optional[str] = Field(None, description="""General description of the experiment.""")
-    experimenter: Optional[NWBFileGeneralExperimenter] = Field(None, description="""Name of person(s) who performed the experiment. Can also specify roles of different people involved.""")
+    experimenter: Optional[List[str]] = Field(default_factory=list, description="""Name of person(s) who performed the experiment. Can also specify roles of different people involved.""")
     institution: Optional[str] = Field(None, description="""Institution(s) where experiment was performed.""")
-    keywords: Optional[NWBFileGeneralKeywords] = Field(None, description="""Terms to search over.""")
+    keywords: Optional[List[str]] = Field(default_factory=list, description="""Terms to search over.""")
     lab: Optional[str] = Field(None, description="""Laboratory where experiment was performed.""")
     notes: Optional[str] = Field(None, description="""Notes about the experiment.""")
     pharmacology: Optional[str] = Field(None, description="""Description of drugs used, including how and when they were administered. Anesthesia(s), painkiller(s), etc., plus dosage, concentration, etc.""")
     protocol: Optional[str] = Field(None, description="""Experimental protocol, if applicable. e.g., include IACUC protocol number.""")
-    related_publications: Optional[NWBFileGeneralRelatedPublications] = Field(None, description="""Publication information. PMID, DOI, URL, etc.""")
+    related_publications: Optional[List[str]] = Field(default_factory=list, description="""Publication information. PMID, DOI, URL, etc.""")
     session_id: Optional[str] = Field(None, description="""Lab-specific ID for the session.""")
     slices: Optional[str] = Field(None, description="""Description of slices, including information about preparation thickness, orientation, temperature, and bath solution.""")
     source_script: Optional[NWBFileGeneralSourceScript] = Field(None, description="""Script file or link to public source code used to create this NWB file.""")
     stimulus: Optional[str] = Field(None, description="""Notes about stimuli, such as how and where they were presented.""")
     surgery: Optional[str] = Field(None, description="""Narrative description about surgery/surgeries, including date(s) and who performed surgery.""")
     virus: Optional[str] = Field(None, description="""Information about virus(es) used in experiments, including virus ID, source, date made, injection location, volume, etc.""")
-    LabMetaData: Optional[List[LabMetaData]] = Field(default_factory=list, description="""Place-holder than can be extended so that lab-specific meta-data can be placed in /general.""")
-    devices: Optional[NWBFileGeneralDevices] = Field(None, description="""Description of hardware devices used during experiment, e.g., monitors, ADC boards, microscopes, etc.""")
-    subject: Optional[NWBFileGeneralSubject] = Field(None, description="""Information about the animal or person from which the data was measured.""")
+    lab_meta_data: Optional[List[LabMetaData]] = Field(default_factory=list, description="""Place-holder than can be extended so that lab-specific meta-data can be placed in /general.""")
+    devices: Optional[List[Device]] = Field(default_factory=list, description="""Description of hardware devices used during experiment, e.g., monitors, ADC boards, microscopes, etc.""")
+    subject: Optional[Subject] = Field(None, description="""Information about the animal or person from which the data was measured.""")
     extracellular_ephys: Optional[NWBFileGeneralExtracellularEphys] = Field(None, description="""Metadata related to extracellular electrophysiology.""")
     intracellular_ephys: Optional[NWBFileGeneralIntracellularEphys] = Field(None, description="""Metadata related to intracellular electrophysiology.""")
-    optogenetics: Optional[NWBFileGeneralOptogenetics] = Field(None, description="""Metadata describing optogenetic stimuluation.""")
-    optophysiology: Optional[NWBFileGeneralOptophysiology] = Field(None, description="""Metadata related to optophysiology.""")
-    
-
-class NWBFileGeneralExperimenter(ConfiguredBaseModel):
-    """
-    Name of person(s) who performed the experiment. Can also specify roles of different people involved.
-    """
-    experimenter: Optional[List[str]] = Field(default_factory=list, description="""Name of person(s) who performed the experiment. Can also specify roles of different people involved.""")
-    
-
-class NWBFileGeneralKeywords(ConfiguredBaseModel):
-    """
-    Terms to search over.
-    """
-    keywords: Optional[List[str]] = Field(default_factory=list, description="""Terms to search over.""")
-    
-
-class NWBFileGeneralRelatedPublications(ConfiguredBaseModel):
-    """
-    Publication information. PMID, DOI, URL, etc.
-    """
-    related_publications: Optional[List[str]] = Field(default_factory=list, description="""Publication information. PMID, DOI, URL, etc.""")
+    optogenetics: Optional[List[OptogeneticStimulusSite]] = Field(default_factory=list, description="""Metadata describing optogenetic stimuluation.""")
+    optophysiology: Optional[List[ImagingPlane]] = Field(default_factory=list, description="""Metadata related to optophysiology.""")
     
 
 class NWBFileGeneralSourceScript(ConfiguredBaseModel):
     """
     Script file or link to public source code used to create this NWB file.
     """
+    name: str = Field("source_script", const=True)
     file_name: Optional[str] = Field(None, description="""Name of script file.""")
     
 
-class NWBFileGeneralDevices(ConfiguredBaseModel):
-    """
-    Description of hardware devices used during experiment, e.g., monitors, ADC boards, microscopes, etc.
-    """
-    Device: Optional[List[Device]] = Field(default_factory=list, description="""Data acquisition devices.""")
-    
-
-class NWBFileGeneralSubject(Subject):
-    """
-    Information about the animal or person from which the data was measured.
-    """
-    age: Optional[SubjectAge] = Field(None, description="""Age of subject. Can be supplied instead of 'date_of_birth'.""")
-    date_of_birth: Optional[date] = Field(None, description="""Date of birth of subject. Can be supplied instead of 'age'.""")
-    description: Optional[str] = Field(None, description="""Description of subject and where subject came from (e.g., breeder, if animal).""")
-    genotype: Optional[str] = Field(None, description="""Genetic strain. If absent, assume Wild Type (WT).""")
-    sex: Optional[str] = Field(None, description="""Gender of subject.""")
-    species: Optional[str] = Field(None, description="""Species of subject.""")
-    strain: Optional[str] = Field(None, description="""Strain of subject.""")
-    subject_id: Optional[str] = Field(None, description="""ID of animal/person used/participating in experiment (lab convention).""")
-    weight: Optional[str] = Field(None, description="""Weight at time of experiment, at time of surgery and at other important times.""")
-    
-
 class NWBFileGeneralExtracellularEphys(ConfiguredBaseModel):
     """
     Metadata related to extracellular electrophysiology.
     """
-    ElectrodeGroup: Optional[List[ElectrodeGroup]] = Field(default_factory=list, description="""Physical group of electrodes.""")
-    electrodes: Optional[NWBFileGeneralExtracellularEphysElectrodes] = Field(None, description="""A table of all electrodes (i.e. channels) used for recording.""")
-    
-
-class NWBFileGeneralExtracellularEphysElectrodes(DynamicTable):
-    """
-    A table of all electrodes (i.e. channels) used for recording.
-    """
-    x: Optional[List[float]] = Field(default_factory=list, description="""x coordinate of the channel location in the brain (+x is posterior).""")
-    y: Optional[List[float]] = Field(default_factory=list, description="""y coordinate of the channel location in the brain (+y is inferior).""")
-    z: Optional[List[float]] = Field(default_factory=list, description="""z coordinate of the channel location in the brain (+z is right).""")
-    imp: Optional[List[float]] = Field(default_factory=list, description="""Impedance of the channel, in ohms.""")
-    location: Optional[List[str]] = Field(default_factory=list, description="""Location of the electrode (channel). Specify the area, layer, comments on estimation of area/layer, stereotaxic coordinates if in vivo, etc. Use standard atlas names for anatomical regions when possible.""")
-    filtering: Optional[List[str]] = Field(default_factory=list, description="""Description of hardware filtering, including the filter name and frequency cutoffs.""")
-    group: Optional[List[ElectrodeGroup]] = Field(default_factory=list, description="""Reference to the ElectrodeGroup this electrode is a part of.""")
-    group_name: Optional[List[str]] = Field(default_factory=list, description="""Name of the ElectrodeGroup this electrode is a part of.""")
-    rel_x: Optional[List[float]] = Field(default_factory=list, description="""x coordinate in electrode group""")
-    rel_y: Optional[List[float]] = Field(default_factory=list, description="""y coordinate in electrode group""")
-    rel_z: Optional[List[float]] = Field(default_factory=list, description="""z coordinate in electrode group""")
-    reference: Optional[List[str]] = Field(default_factory=list, description="""Description of the reference electrode and/or reference scheme used for this electrode, e.g., \"stainless steel skull screw\" or \"online common average referencing\".""")
-    colnames: Optional[str] = Field(None, description="""The names of the columns in this table. This should be used to specify an order to the columns.""")
-    description: Optional[str] = Field(None, description="""Description of what is in this dynamic table.""")
-    id: DynamicTableId = Field(..., description="""Array of unique identifiers for the rows of this dynamic table.""")
-    VectorData: Optional[List[VectorData]] = Field(default_factory=list, description="""Vector columns, including index columns, of this dynamic table.""")
+    name: str = Field("extracellular_ephys", const=True)
+    electrode_group: Optional[List[ElectrodeGroup]] = Field(default_factory=list, description="""Physical group of electrodes.""")
+    electrodes: Optional[DynamicTable] = Field(None, description="""A table of all electrodes (i.e. channels) used for recording.""")
     
 
 class NWBFileGeneralIntracellularEphys(ConfiguredBaseModel):
     """
     Metadata related to intracellular electrophysiology.
     """
+    name: str = Field("intracellular_ephys", const=True)
     filtering: Optional[str] = Field(None, description="""[DEPRECATED] Use IntracellularElectrode.filtering instead. Description of filtering used. Includes filtering type and parameters, frequency fall-off, etc. If this changes between TimeSeries, filter description should be stored as a text attribute for each TimeSeries.""")
-    IntracellularElectrode: Optional[List[IntracellularElectrode]] = Field(default_factory=list, description="""An intracellular electrode.""")
-    sweep_table: Optional[NWBFileGeneralIntracellularEphysSweepTable] = Field(None, description="""[DEPRECATED] Table used to group different PatchClampSeries. SweepTable is being replaced by IntracellularRecordingsTable and SimultaneousRecordingsTable tables. Additional SequentialRecordingsTable, RepetitionsTable and ExperimentalConditions tables provide enhanced support for experiment metadata.""")
-    intracellular_recordings: Optional[NWBFileGeneralIntracellularEphysIntracellularRecordings] = Field(None, description="""A table to group together a stimulus and response from a single electrode and a single simultaneous recording. Each row in the table represents a single recording consisting typically of a stimulus and a corresponding response. In some cases, however, only a stimulus or a response are recorded as as part of an experiment. In this case both, the stimulus and response will point to the same TimeSeries while the idx_start and count of the invalid column will be set to -1, thus, indicating that no values have been recorded for the stimulus or response, respectively. Note, a recording MUST contain at least a stimulus or a response. Typically the stimulus and response are PatchClampSeries. However, the use of AD/DA channels that are not associated to an electrode is also common in intracellular electrophysiology, in which case other TimeSeries may be used.""")
-    simultaneous_recordings: Optional[NWBFileGeneralIntracellularEphysSimultaneousRecordings] = Field(None, description="""A table for grouping different intracellular recordings from the IntracellularRecordingsTable table together that were recorded simultaneously from different electrodes""")
-    sequential_recordings: Optional[NWBFileGeneralIntracellularEphysSequentialRecordings] = Field(None, description="""A table for grouping different sequential recordings from the SimultaneousRecordingsTable table together. This is typically used to group together sequential recordings where the a sequence of stimuli of the same type with varying parameters have been presented in a sequence.""")
-    repetitions: Optional[NWBFileGeneralIntracellularEphysRepetitions] = Field(None, description="""A table for grouping different sequential intracellular recordings together. With each SequentialRecording typically representing a particular type of stimulus, the RepetitionsTable table is typically used to group sets of stimuli applied in sequence.""")
-    experimental_conditions: Optional[NWBFileGeneralIntracellularEphysExperimentalConditions] = Field(None, description="""A table for grouping different intracellular recording repetitions together that belong to the same experimental experimental_conditions.""")
-    
-
-class NWBFileGeneralIntracellularEphysSweepTable(SweepTable):
-    """
-    [DEPRECATED] Table used to group different PatchClampSeries. SweepTable is being replaced by IntracellularRecordingsTable and SimultaneousRecordingsTable tables. Additional SequentialRecordingsTable, RepetitionsTable and ExperimentalConditions tables provide enhanced support for experiment metadata.
-    """
-    sweep_number: Optional[List[int]] = Field(default_factory=list, description="""Sweep number of the PatchClampSeries in that row.""")
-    series: Optional[List[PatchClampSeries]] = Field(default_factory=list, description="""The PatchClampSeries with the sweep number in that row.""")
-    series_index: SweepTableSeriesIndex = Field(..., description="""Index for series.""")
-    colnames: Optional[str] = Field(None, description="""The names of the columns in this table. This should be used to specify an order to the columns.""")
-    description: Optional[str] = Field(None, description="""Description of what is in this dynamic table.""")
-    id: DynamicTableId = Field(..., description="""Array of unique identifiers for the rows of this dynamic table.""")
-    VectorData: Optional[List[VectorData]] = Field(default_factory=list, description="""Vector columns, including index columns, of this dynamic table.""")
-    
-
-class NWBFileGeneralIntracellularEphysIntracellularRecordings(IntracellularRecordingsTable):
-    """
-    A table to group together a stimulus and response from a single electrode and a single simultaneous recording. Each row in the table represents a single recording consisting typically of a stimulus and a corresponding response. In some cases, however, only a stimulus or a response are recorded as as part of an experiment. In this case both, the stimulus and response will point to the same TimeSeries while the idx_start and count of the invalid column will be set to -1, thus, indicating that no values have been recorded for the stimulus or response, respectively. Note, a recording MUST contain at least a stimulus or a response. Typically the stimulus and response are PatchClampSeries. However, the use of AD/DA channels that are not associated to an electrode is also common in intracellular electrophysiology, in which case other TimeSeries may be used.
-    """
-    description: Optional[str] = Field(None, description="""Description of the contents of this table. Inherited from AlignedDynamicTable and overwritten here to fix the value of the attribute.""")
-    electrodes: IntracellularRecordingsTableElectrodes = Field(..., description="""Table for storing intracellular electrode related metadata.""")
-    stimuli: IntracellularRecordingsTableStimuli = Field(..., description="""Table for storing intracellular stimulus related metadata.""")
-    responses: IntracellularRecordingsTableResponses = Field(..., description="""Table for storing intracellular response related metadata.""")
-    categories: Optional[str] = Field(None, description="""The names of the categories in this AlignedDynamicTable. Each category is represented by one DynamicTable stored in the parent group. This attribute should be used to specify an order of categories and the category names must match the names of the corresponding DynamicTable in the group.""")
-    DynamicTable: Optional[List[DynamicTable]] = Field(default_factory=list, description="""A DynamicTable representing a particular category for columns in the AlignedDynamicTable parent container. The table MUST be aligned with (i.e., have the same number of rows) as all other DynamicTables stored in the AlignedDynamicTable parent container. The name of the category is given by the name of the DynamicTable and its description by the description attribute of the DynamicTable.""")
-    colnames: Optional[str] = Field(None, description="""The names of the columns in this table. This should be used to specify an order to the columns.""")
-    id: DynamicTableId = Field(..., description="""Array of unique identifiers for the rows of this dynamic table.""")
-    VectorData: Optional[List[VectorData]] = Field(default_factory=list, description="""Vector columns, including index columns, of this dynamic table.""")
-    
-
-class NWBFileGeneralIntracellularEphysSimultaneousRecordings(SimultaneousRecordingsTable):
-    """
-    A table for grouping different intracellular recordings from the IntracellularRecordingsTable table together that were recorded simultaneously from different electrodes
-    """
-    recordings: SimultaneousRecordingsTableRecordings = Field(..., description="""A reference to one or more rows in the IntracellularRecordingsTable table.""")
-    recordings_index: SimultaneousRecordingsTableRecordingsIndex = Field(..., description="""Index dataset for the recordings column.""")
-    colnames: Optional[str] = Field(None, description="""The names of the columns in this table. This should be used to specify an order to the columns.""")
-    description: Optional[str] = Field(None, description="""Description of what is in this dynamic table.""")
-    id: DynamicTableId = Field(..., description="""Array of unique identifiers for the rows of this dynamic table.""")
-    VectorData: Optional[List[VectorData]] = Field(default_factory=list, description="""Vector columns, including index columns, of this dynamic table.""")
-    
-
-class NWBFileGeneralIntracellularEphysSequentialRecordings(SequentialRecordingsTable):
-    """
-    A table for grouping different sequential recordings from the SimultaneousRecordingsTable table together. This is typically used to group together sequential recordings where the a sequence of stimuli of the same type with varying parameters have been presented in a sequence.
-    """
-    simultaneous_recordings: SequentialRecordingsTableSimultaneousRecordings = Field(..., description="""A reference to one or more rows in the SimultaneousRecordingsTable table.""")
-    simultaneous_recordings_index: SequentialRecordingsTableSimultaneousRecordingsIndex = Field(..., description="""Index dataset for the simultaneous_recordings column.""")
-    stimulus_type: Optional[List[str]] = Field(default_factory=list, description="""The type of stimulus used for the sequential recording.""")
-    colnames: Optional[str] = Field(None, description="""The names of the columns in this table. This should be used to specify an order to the columns.""")
-    description: Optional[str] = Field(None, description="""Description of what is in this dynamic table.""")
-    id: DynamicTableId = Field(..., description="""Array of unique identifiers for the rows of this dynamic table.""")
-    VectorData: Optional[List[VectorData]] = Field(default_factory=list, description="""Vector columns, including index columns, of this dynamic table.""")
-    
-
-class NWBFileGeneralIntracellularEphysRepetitions(RepetitionsTable):
-    """
-    A table for grouping different sequential intracellular recordings together. With each SequentialRecording typically representing a particular type of stimulus, the RepetitionsTable table is typically used to group sets of stimuli applied in sequence.
-    """
-    sequential_recordings: RepetitionsTableSequentialRecordings = Field(..., description="""A reference to one or more rows in the SequentialRecordingsTable table.""")
-    sequential_recordings_index: RepetitionsTableSequentialRecordingsIndex = Field(..., description="""Index dataset for the sequential_recordings column.""")
-    colnames: Optional[str] = Field(None, description="""The names of the columns in this table. This should be used to specify an order to the columns.""")
-    description: Optional[str] = Field(None, description="""Description of what is in this dynamic table.""")
-    id: DynamicTableId = Field(..., description="""Array of unique identifiers for the rows of this dynamic table.""")
-    VectorData: Optional[List[VectorData]] = Field(default_factory=list, description="""Vector columns, including index columns, of this dynamic table.""")
-    
-
-class NWBFileGeneralIntracellularEphysExperimentalConditions(ExperimentalConditionsTable):
-    """
-    A table for grouping different intracellular recording repetitions together that belong to the same experimental experimental_conditions.
-    """
-    repetitions: ExperimentalConditionsTableRepetitions = Field(..., description="""A reference to one or more rows in the RepetitionsTable table.""")
-    repetitions_index: ExperimentalConditionsTableRepetitionsIndex = Field(..., description="""Index dataset for the repetitions column.""")
-    colnames: Optional[str] = Field(None, description="""The names of the columns in this table. This should be used to specify an order to the columns.""")
-    description: Optional[str] = Field(None, description="""Description of what is in this dynamic table.""")
-    id: DynamicTableId = Field(..., description="""Array of unique identifiers for the rows of this dynamic table.""")
-    VectorData: Optional[List[VectorData]] = Field(default_factory=list, description="""Vector columns, including index columns, of this dynamic table.""")
-    
-
-class NWBFileGeneralOptogenetics(ConfiguredBaseModel):
-    """
-    Metadata describing optogenetic stimuluation.
-    """
-    OptogeneticStimulusSite: Optional[List[OptogeneticStimulusSite]] = Field(default_factory=list, description="""An optogenetic stimulation site.""")
-    
-
-class NWBFileGeneralOptophysiology(ConfiguredBaseModel):
-    """
-    Metadata related to optophysiology.
-    """
-    ImagingPlane: Optional[List[ImagingPlane]] = Field(default_factory=list, description="""An imaging plane.""")
+    intracellular_electrode: Optional[List[IntracellularElectrode]] = Field(default_factory=list, description="""An intracellular electrode.""")
+    sweep_table: Optional[SweepTable] = Field(None, description="""[DEPRECATED] Table used to group different PatchClampSeries. SweepTable is being replaced by IntracellularRecordingsTable and SimultaneousRecordingsTable tables. Additional SequentialRecordingsTable, RepetitionsTable and ExperimentalConditions tables provide enhanced support for experiment metadata.""")
+    intracellular_recordings: Optional[IntracellularRecordingsTable] = Field(None, description="""A table to group together a stimulus and response from a single electrode and a single simultaneous recording. Each row in the table represents a single recording consisting typically of a stimulus and a corresponding response. In some cases, however, only a stimulus or a response are recorded as as part of an experiment. In this case both, the stimulus and response will point to the same TimeSeries while the idx_start and count of the invalid column will be set to -1, thus, indicating that no values have been recorded for the stimulus or response, respectively. Note, a recording MUST contain at least a stimulus or a response. Typically the stimulus and response are PatchClampSeries. However, the use of AD/DA channels that are not associated to an electrode is also common in intracellular electrophysiology, in which case other TimeSeries may be used.""")
+    simultaneous_recordings: Optional[SimultaneousRecordingsTable] = Field(None, description="""A table for grouping different intracellular recordings from the IntracellularRecordingsTable table together that were recorded simultaneously from different electrodes""")
+    sequential_recordings: Optional[SequentialRecordingsTable] = Field(None, description="""A table for grouping different sequential recordings from the SimultaneousRecordingsTable table together. This is typically used to group together sequential recordings where the a sequence of stimuli of the same type with varying parameters have been presented in a sequence.""")
+    repetitions: Optional[RepetitionsTable] = Field(None, description="""A table for grouping different sequential intracellular recordings together. With each SequentialRecording typically representing a particular type of stimulus, the RepetitionsTable table is typically used to group sets of stimuli applied in sequence.""")
+    experimental_conditions: Optional[ExperimentalConditionsTable] = Field(None, description="""A table for grouping different intracellular recording repetitions together that belong to the same experimental experimental_conditions.""")
     
 
 class NWBFileIntervals(ConfiguredBaseModel):
     """
     Experimental intervals, whether that be logically distinct sub-experiments having a particular scientific goal, trials (see trials subgroup) during an experiment, or epochs (see epochs subgroup) deriving from analysis of data.
     """
-    epochs: Optional[NWBFileIntervalsEpochs] = Field(None, description="""Divisions in time marking experimental stages or sub-divisions of a single recording session.""")
-    trials: Optional[NWBFileIntervalsTrials] = Field(None, description="""Repeated experimental events that have a logical grouping.""")
-    invalid_times: Optional[NWBFileIntervalsInvalidTimes] = Field(None, description="""Time intervals that should be removed from analysis.""")
-    TimeIntervals: Optional[List[TimeIntervals]] = Field(default_factory=list, description="""Optional additional table(s) for describing other experimental time intervals.""")
-    
-
-class NWBFileIntervalsEpochs(TimeIntervals):
-    """
-    Divisions in time marking experimental stages or sub-divisions of a single recording session.
-    """
-    start_time: Optional[List[float]] = Field(default_factory=list, description="""Start time of epoch, in seconds.""")
-    stop_time: Optional[List[float]] = Field(default_factory=list, description="""Stop time of epoch, in seconds.""")
-    tags: Optional[List[str]] = Field(default_factory=list, description="""User-defined tags that identify or categorize events.""")
-    tags_index: Optional[TimeIntervalsTagsIndex] = Field(None, description="""Index for tags.""")
-    timeseries: Optional[TimeIntervalsTimeseries] = Field(None, description="""An index into a TimeSeries object.""")
-    timeseries_index: Optional[TimeIntervalsTimeseriesIndex] = Field(None, description="""Index for timeseries.""")
-    colnames: Optional[str] = Field(None, description="""The names of the columns in this table. This should be used to specify an order to the columns.""")
-    description: Optional[str] = Field(None, description="""Description of what is in this dynamic table.""")
-    id: DynamicTableId = Field(..., description="""Array of unique identifiers for the rows of this dynamic table.""")
-    VectorData: Optional[List[VectorData]] = Field(default_factory=list, description="""Vector columns, including index columns, of this dynamic table.""")
-    
-
-class NWBFileIntervalsTrials(TimeIntervals):
-    """
-    Repeated experimental events that have a logical grouping.
-    """
-    start_time: Optional[List[float]] = Field(default_factory=list, description="""Start time of epoch, in seconds.""")
-    stop_time: Optional[List[float]] = Field(default_factory=list, description="""Stop time of epoch, in seconds.""")
-    tags: Optional[List[str]] = Field(default_factory=list, description="""User-defined tags that identify or categorize events.""")
-    tags_index: Optional[TimeIntervalsTagsIndex] = Field(None, description="""Index for tags.""")
-    timeseries: Optional[TimeIntervalsTimeseries] = Field(None, description="""An index into a TimeSeries object.""")
-    timeseries_index: Optional[TimeIntervalsTimeseriesIndex] = Field(None, description="""Index for timeseries.""")
-    colnames: Optional[str] = Field(None, description="""The names of the columns in this table. This should be used to specify an order to the columns.""")
-    description: Optional[str] = Field(None, description="""Description of what is in this dynamic table.""")
-    id: DynamicTableId = Field(..., description="""Array of unique identifiers for the rows of this dynamic table.""")
-    VectorData: Optional[List[VectorData]] = Field(default_factory=list, description="""Vector columns, including index columns, of this dynamic table.""")
-    
-
-class NWBFileIntervalsInvalidTimes(TimeIntervals):
-    """
-    Time intervals that should be removed from analysis.
-    """
-    start_time: Optional[List[float]] = Field(default_factory=list, description="""Start time of epoch, in seconds.""")
-    stop_time: Optional[List[float]] = Field(default_factory=list, description="""Stop time of epoch, in seconds.""")
-    tags: Optional[List[str]] = Field(default_factory=list, description="""User-defined tags that identify or categorize events.""")
-    tags_index: Optional[TimeIntervalsTagsIndex] = Field(None, description="""Index for tags.""")
-    timeseries: Optional[TimeIntervalsTimeseries] = Field(None, description="""An index into a TimeSeries object.""")
-    timeseries_index: Optional[TimeIntervalsTimeseriesIndex] = Field(None, description="""Index for timeseries.""")
-    colnames: Optional[str] = Field(None, description="""The names of the columns in this table. This should be used to specify an order to the columns.""")
-    description: Optional[str] = Field(None, description="""Description of what is in this dynamic table.""")
-    id: DynamicTableId = Field(..., description="""Array of unique identifiers for the rows of this dynamic table.""")
-    VectorData: Optional[List[VectorData]] = Field(default_factory=list, description="""Vector columns, including index columns, of this dynamic table.""")
-    
-
-class NWBFileUnits(Units):
-    """
-    Data about sorted spike units.
-    """
-    spike_times_index: Optional[UnitsSpikeTimesIndex] = Field(None, description="""Index into the spike_times dataset.""")
-    spike_times: Optional[UnitsSpikeTimes] = Field(None, description="""Spike times for each unit in seconds.""")
-    obs_intervals_index: Optional[UnitsObsIntervalsIndex] = Field(None, description="""Index into the obs_intervals dataset.""")
-    obs_intervals: Optional[UnitsObsIntervals] = Field(None, description="""Observation intervals for each unit.""")
-    electrodes_index: Optional[UnitsElectrodesIndex] = Field(None, description="""Index into electrodes.""")
-    electrodes: Optional[UnitsElectrodes] = Field(None, description="""Electrode that each spike unit came from, specified using a DynamicTableRegion.""")
-    electrode_group: Optional[List[ElectrodeGroup]] = Field(default_factory=list, description="""Electrode group that each spike unit came from.""")
-    waveform_mean: Optional[UnitsWaveformMean] = Field(None, description="""Spike waveform mean for each spike unit.""")
-    waveform_sd: Optional[UnitsWaveformSd] = Field(None, description="""Spike waveform standard deviation for each spike unit.""")
-    waveforms: Optional[UnitsWaveforms] = Field(None, description="""Individual waveforms for each spike on each electrode. This is a doubly indexed column. The 'waveforms_index' column indexes which waveforms in this column belong to the same spike event for a given unit, where each waveform was recorded from a different electrode. The 'waveforms_index_index' column indexes the 'waveforms_index' column to indicate which spike events belong to a given unit. For example, if the 'waveforms_index_index' column has values [2, 5, 6], then the first 2 elements of the 'waveforms_index' column correspond to the 2 spike events of the first unit, the next 3 elements of the 'waveforms_index' column correspond to the 3 spike events of the second unit, and the next 1 element of the 'waveforms_index' column corresponds to the 1 spike event of the third unit. If the 'waveforms_index' column has values [3, 6, 8, 10, 12, 13], then the first 3 elements of the 'waveforms' column contain the 3 spike waveforms that were recorded from 3 different electrodes for the first spike time of the first unit. See https://nwb-schema.readthedocs.io/en/stable/format_description.html#doubly-ragged-arrays for a graphical representation of this example. When there is only one electrode for each unit (i.e., each spike time is associated with a single waveform), then the 'waveforms_index' column will have values 1, 2, ..., N, where N is the number of spike events. The number of electrodes for each spike event should be the same within a given unit. The 'electrodes' column should be used to indicate which electrodes are associated with each unit, and the order of the waveforms within a given unit x spike event should be in the same order as the electrodes referenced in the 'electrodes' column of this table. The number of samples for each waveform must be the same.""")
-    waveforms_index: Optional[UnitsWaveformsIndex] = Field(None, description="""Index into the waveforms dataset. One value for every spike event. See 'waveforms' for more detail.""")
-    waveforms_index_index: Optional[UnitsWaveformsIndexIndex] = Field(None, description="""Index into the waveforms_index dataset. One value for every unit (row in the table). See 'waveforms' for more detail.""")
-    colnames: Optional[str] = Field(None, description="""The names of the columns in this table. This should be used to specify an order to the columns.""")
-    description: Optional[str] = Field(None, description="""Description of what is in this dynamic table.""")
-    id: DynamicTableId = Field(..., description="""Array of unique identifiers for the rows of this dynamic table.""")
-    VectorData: Optional[List[VectorData]] = Field(default_factory=list, description="""Vector columns, including index columns, of this dynamic table.""")
+    name: str = Field("intervals", const=True)
+    epochs: Optional[TimeIntervals] = Field(None, description="""Divisions in time marking experimental stages or sub-divisions of a single recording session.""")
+    trials: Optional[TimeIntervals] = Field(None, description="""Repeated experimental events that have a logical grouping.""")
+    invalid_times: Optional[TimeIntervals] = Field(None, description="""Time intervals that should be removed from analysis.""")
+    time_intervals: Optional[List[TimeIntervals]] = Field(default_factory=list, description="""Optional additional table(s) for describing other experimental time intervals.""")
     
 
 class SubjectAge(ConfiguredBaseModel):
     """
     Age of subject. Can be supplied instead of 'date_of_birth'.
     """
+    name: str = Field("age", const=True)
     reference: Optional[str] = Field(None, description="""Age is with reference to this event. Can be 'birth' or 'gestational'. If reference is omitted, 'birth' is implied.""")
     
 
 
-# Update forward refs
-# see https://pydantic-docs.helpmanual.io/usage/postponed_annotations/
-NWBFileFileCreateDate.update_forward_refs()
-NWBFileAcquisition.update_forward_refs()
-NWBFileAnalysis.update_forward_refs()
-NWBFileScratch.update_forward_refs()
-NWBFileProcessing.update_forward_refs()
-NWBFileStimulus.update_forward_refs()
-NWBFileStimulusPresentation.update_forward_refs()
-NWBFileStimulusTemplates.update_forward_refs()
-NWBFileGeneral.update_forward_refs()
-NWBFileGeneralExperimenter.update_forward_refs()
-NWBFileGeneralKeywords.update_forward_refs()
-NWBFileGeneralRelatedPublications.update_forward_refs()
-NWBFileGeneralSourceScript.update_forward_refs()
-NWBFileGeneralDevices.update_forward_refs()
-NWBFileGeneralSubject.update_forward_refs()
-NWBFileGeneralExtracellularEphys.update_forward_refs()
-NWBFileGeneralExtracellularEphysElectrodes.update_forward_refs()
-NWBFileGeneralIntracellularEphys.update_forward_refs()
-NWBFileGeneralIntracellularEphysSweepTable.update_forward_refs()
-NWBFileGeneralIntracellularEphysIntracellularRecordings.update_forward_refs()
-NWBFileGeneralIntracellularEphysSimultaneousRecordings.update_forward_refs()
-NWBFileGeneralIntracellularEphysSequentialRecordings.update_forward_refs()
-NWBFileGeneralIntracellularEphysRepetitions.update_forward_refs()
-NWBFileGeneralIntracellularEphysExperimentalConditions.update_forward_refs()
-NWBFileGeneralOptogenetics.update_forward_refs()
-NWBFileGeneralOptophysiology.update_forward_refs()
-NWBFileIntervals.update_forward_refs()
-NWBFileIntervalsEpochs.update_forward_refs()
-NWBFileIntervalsTrials.update_forward_refs()
-NWBFileIntervalsInvalidTimes.update_forward_refs()
-NWBFileUnits.update_forward_refs()
-SubjectAge.update_forward_refs()
+# Model rebuild
+# see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
+NWBFileStimulus.model_rebuild()
+NWBFileGeneral.model_rebuild()
+NWBFileGeneralSourceScript.model_rebuild()
+NWBFileGeneralExtracellularEphys.model_rebuild()
+NWBFileGeneralIntracellularEphys.model_rebuild()
+NWBFileIntervals.model_rebuild()
+SubjectAge.model_rebuild()
+    

nwb_linkml/models/core_nwb_icephys.py

@@ -11,42 +11,38 @@ else:
     from typing_extensions import Literal
 
 
-from .core_nwb_icephys_include import (
-    IntracellularRecordingsTableResponses,
-    VoltageClampSeriesResistanceCompBandwidth,
-    RepetitionsTableSequentialRecordingsIndex,
-    ExperimentalConditionsTableRepetitionsIndex,
-    SequentialRecordingsTableSimultaneousRecordingsIndex,
-    IntracellularResponsesTableResponse,
-    VoltageClampSeriesWholeCellCapacitanceComp,
-    CurrentClampStimulusSeriesData,
-    IntracellularRecordingsTableElectrodes,
-    RepetitionsTableSequentialRecordings,
-    VoltageClampSeriesCapacitanceSlow,
-    IntracellularStimuliTableStimulus,
-    VoltageClampSeriesWholeCellSeriesResistanceComp,
-    VoltageClampSeriesData,
-    ExperimentalConditionsTableRepetitions,
-    PatchClampSeriesData,
-    VoltageClampSeriesResistanceCompPrediction,
-    IntracellularRecordingsTableStimuli,
-    CurrentClampSeriesData,
-    SimultaneousRecordingsTableRecordingsIndex,
-    SequentialRecordingsTableSimultaneousRecordings,
-    VoltageClampStimulusSeriesData,
-    VoltageClampSeriesResistanceCompCorrection,
-    SweepTableSeriesIndex,
-    VoltageClampSeriesCapacitanceFast,
-    SimultaneousRecordingsTableRecordings
-)
-
 from .core_nwb_base import (
     TimeSeries,
-    NWBContainer,
-    DynamicTable
+    NWBContainer
+)
+
+from .core_nwb_icephys_include import (
+    VoltageClampSeriesCapacitanceSlow,
+    ExperimentalConditionsTableRepetitions,
+    VoltageClampStimulusSeriesData,
+    ExperimentalConditionsTableRepetitionsIndex,
+    VoltageClampSeriesResistanceCompPrediction,
+    VoltageClampSeriesWholeCellSeriesResistanceComp,
+    SequentialRecordingsTableSimultaneousRecordings,
+    VoltageClampSeriesCapacitanceFast,
+    RepetitionsTableSequentialRecordingsIndex,
+    IntracellularStimuliTableStimulus,
+    VoltageClampSeriesResistanceCompCorrection,
+    SequentialRecordingsTableSimultaneousRecordingsIndex,
+    SimultaneousRecordingsTableRecordings,
+    IntracellularResponsesTableResponse,
+    VoltageClampSeriesResistanceCompBandwidth,
+    CurrentClampSeriesData,
+    SimultaneousRecordingsTableRecordingsIndex,
+    VoltageClampSeriesData,
+    RepetitionsTableSequentialRecordings,
+    VoltageClampSeriesWholeCellCapacitanceComp,
+    CurrentClampStimulusSeriesData,
+    SweepTableSeriesIndex
 )
 
 from .hdmf_common_table import (
+    DynamicTable,
     AlignedDynamicTable
 )
 
@@ -54,13 +50,9 @@ from .hdmf_common_table import (
 metamodel_version = "None"
 version = "None"
 
-class WeakRefShimBaseModel(BaseModel):
-   __slots__ = '__weakref__'
-
-class ConfiguredBaseModel(WeakRefShimBaseModel,
+class ConfiguredBaseModel(BaseModel,
                 validate_assignment = True,
-                validate_all = True,
-                underscore_attrs_are_private = True,
+                validate_default = True,
                 extra = 'forbid',
                 arbitrary_types_allowed = True,
                 use_enum_values = True):
@@ -71,16 +63,17 @@ class PatchClampSeries(TimeSeries):
     """
     An abstract base class for patch-clamp data - stimulus or response, current or voltage.
     """
+    name: str = Field(...)
     stimulus_description: Optional[str] = Field(None, description="""Protocol/stimulus name for this patch-clamp dataset.""")
     sweep_number: Optional[int] = Field(None, description="""Sweep number, allows to group different PatchClampSeries together.""")
-    data: PatchClampSeriesData = Field(..., description="""Recorded voltage or current.""")
+    data: List[float] = Field(default_factory=list, description="""Recorded voltage or current.""")
     gain: Optional[float] = Field(None, description="""Gain of the recording, in units Volt/Amp (v-clamp) or Volt/Volt (c-clamp).""")
     description: Optional[str] = Field(None, description="""Description of the time series.""")
     comments: Optional[str] = Field(None, description="""Human-readable comments about the TimeSeries. This second descriptive field can be used to store additional information, or descriptive information if the primary description field is populated with a computer-readable string.""")
     starting_time: Optional[TimeSeriesStartingTime] = Field(None, description="""Timestamp of the first sample in seconds. When timestamps are uniformly spaced, the timestamp of the first sample can be specified and all subsequent ones calculated from the sampling rate attribute.""")
-    timestamps: Optional[TimeSeriesTimestamps] = Field(None, description="""Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time.""")
-    control: Optional[TimeSeriesControl] = Field(None, description="""Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data.""")
-    control_description: Optional[TimeSeriesControlDescription] = Field(None, description="""Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0.""")
+    timestamps: Optional[List[float]] = Field(default_factory=list, description="""Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time.""")
+    control: Optional[List[int]] = Field(default_factory=list, description="""Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data.""")
+    control_description: Optional[List[str]] = Field(default_factory=list, description="""Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0.""")
     sync: Optional[TimeSeriesSync] = Field(None, description="""Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of 'sync' are mostly for archival purposes.""")
     
 
@@ -88,6 +81,7 @@ class CurrentClampSeries(PatchClampSeries):
     """
     Voltage data from an intracellular current-clamp recording. A corresponding CurrentClampStimulusSeries (stored separately as a stimulus) is used to store the current injected.
     """
+    name: str = Field(...)
     data: CurrentClampSeriesData = Field(..., description="""Recorded voltage.""")
     bias_current: Optional[float] = Field(None, description="""Bias current, in amps.""")
     bridge_balance: Optional[float] = Field(None, description="""Bridge balance, in ohms.""")
@@ -98,9 +92,9 @@ class CurrentClampSeries(PatchClampSeries):
     description: Optional[str] = Field(None, description="""Description of the time series.""")
     comments: Optional[str] = Field(None, description="""Human-readable comments about the TimeSeries. This second descriptive field can be used to store additional information, or descriptive information if the primary description field is populated with a computer-readable string.""")
     starting_time: Optional[TimeSeriesStartingTime] = Field(None, description="""Timestamp of the first sample in seconds. When timestamps are uniformly spaced, the timestamp of the first sample can be specified and all subsequent ones calculated from the sampling rate attribute.""")
-    timestamps: Optional[TimeSeriesTimestamps] = Field(None, description="""Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time.""")
-    control: Optional[TimeSeriesControl] = Field(None, description="""Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data.""")
-    control_description: Optional[TimeSeriesControlDescription] = Field(None, description="""Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0.""")
+    timestamps: Optional[List[float]] = Field(default_factory=list, description="""Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time.""")
+    control: Optional[List[int]] = Field(default_factory=list, description="""Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data.""")
+    control_description: Optional[List[str]] = Field(default_factory=list, description="""Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0.""")
     sync: Optional[TimeSeriesSync] = Field(None, description="""Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of 'sync' are mostly for archival purposes.""")
     
 
@@ -108,6 +102,7 @@ class IZeroClampSeries(CurrentClampSeries):
     """
     Voltage data from an intracellular recording when all current and amplifier settings are off (i.e., CurrentClampSeries fields will be zero). There is no CurrentClampStimulusSeries associated with an IZero series because the amplifier is disconnected and no stimulus can reach the cell.
     """
+    name: str = Field(...)
     stimulus_description: Optional[str] = Field(None, description="""An IZeroClampSeries has no stimulus, so this attribute is automatically set to \"N/A\"""")
     bias_current: float = Field(..., description="""Bias current, in amps, fixed to 0.0.""")
     bridge_balance: float = Field(..., description="""Bridge balance, in ohms, fixed to 0.0.""")
@@ -118,9 +113,9 @@ class IZeroClampSeries(CurrentClampSeries):
     description: Optional[str] = Field(None, description="""Description of the time series.""")
     comments: Optional[str] = Field(None, description="""Human-readable comments about the TimeSeries. This second descriptive field can be used to store additional information, or descriptive information if the primary description field is populated with a computer-readable string.""")
     starting_time: Optional[TimeSeriesStartingTime] = Field(None, description="""Timestamp of the first sample in seconds. When timestamps are uniformly spaced, the timestamp of the first sample can be specified and all subsequent ones calculated from the sampling rate attribute.""")
-    timestamps: Optional[TimeSeriesTimestamps] = Field(None, description="""Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time.""")
-    control: Optional[TimeSeriesControl] = Field(None, description="""Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data.""")
-    control_description: Optional[TimeSeriesControlDescription] = Field(None, description="""Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0.""")
+    timestamps: Optional[List[float]] = Field(default_factory=list, description="""Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time.""")
+    control: Optional[List[int]] = Field(default_factory=list, description="""Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data.""")
+    control_description: Optional[List[str]] = Field(default_factory=list, description="""Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0.""")
     sync: Optional[TimeSeriesSync] = Field(None, description="""Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of 'sync' are mostly for archival purposes.""")
     
 
@@ -128,6 +123,7 @@ class CurrentClampStimulusSeries(PatchClampSeries):
     """
     Stimulus current applied during current clamp recording.
     """
+    name: str = Field(...)
     data: CurrentClampStimulusSeriesData = Field(..., description="""Stimulus current applied.""")
     stimulus_description: Optional[str] = Field(None, description="""Protocol/stimulus name for this patch-clamp dataset.""")
     sweep_number: Optional[int] = Field(None, description="""Sweep number, allows to group different PatchClampSeries together.""")
@@ -135,9 +131,9 @@ class CurrentClampStimulusSeries(PatchClampSeries):
     description: Optional[str] = Field(None, description="""Description of the time series.""")
     comments: Optional[str] = Field(None, description="""Human-readable comments about the TimeSeries. This second descriptive field can be used to store additional information, or descriptive information if the primary description field is populated with a computer-readable string.""")
     starting_time: Optional[TimeSeriesStartingTime] = Field(None, description="""Timestamp of the first sample in seconds. When timestamps are uniformly spaced, the timestamp of the first sample can be specified and all subsequent ones calculated from the sampling rate attribute.""")
-    timestamps: Optional[TimeSeriesTimestamps] = Field(None, description="""Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time.""")
-    control: Optional[TimeSeriesControl] = Field(None, description="""Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data.""")
-    control_description: Optional[TimeSeriesControlDescription] = Field(None, description="""Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0.""")
+    timestamps: Optional[List[float]] = Field(default_factory=list, description="""Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time.""")
+    control: Optional[List[int]] = Field(default_factory=list, description="""Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data.""")
+    control_description: Optional[List[str]] = Field(default_factory=list, description="""Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0.""")
     sync: Optional[TimeSeriesSync] = Field(None, description="""Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of 'sync' are mostly for archival purposes.""")
     
 
@@ -145,6 +141,7 @@ class VoltageClampSeries(PatchClampSeries):
     """
     Current data from an intracellular voltage-clamp recording. A corresponding VoltageClampStimulusSeries (stored separately as a stimulus) is used to store the voltage injected.
     """
+    name: str = Field(...)
     data: VoltageClampSeriesData = Field(..., description="""Recorded current.""")
     capacitance_fast: Optional[VoltageClampSeriesCapacitanceFast] = Field(None, description="""Fast capacitance, in farads.""")
     capacitance_slow: Optional[VoltageClampSeriesCapacitanceSlow] = Field(None, description="""Slow capacitance, in farads.""")
@@ -159,9 +156,9 @@ class VoltageClampSeries(PatchClampSeries):
     description: Optional[str] = Field(None, description="""Description of the time series.""")
     comments: Optional[str] = Field(None, description="""Human-readable comments about the TimeSeries. This second descriptive field can be used to store additional information, or descriptive information if the primary description field is populated with a computer-readable string.""")
     starting_time: Optional[TimeSeriesStartingTime] = Field(None, description="""Timestamp of the first sample in seconds. When timestamps are uniformly spaced, the timestamp of the first sample can be specified and all subsequent ones calculated from the sampling rate attribute.""")
-    timestamps: Optional[TimeSeriesTimestamps] = Field(None, description="""Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time.""")
-    control: Optional[TimeSeriesControl] = Field(None, description="""Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data.""")
-    control_description: Optional[TimeSeriesControlDescription] = Field(None, description="""Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0.""")
+    timestamps: Optional[List[float]] = Field(default_factory=list, description="""Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time.""")
+    control: Optional[List[int]] = Field(default_factory=list, description="""Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data.""")
+    control_description: Optional[List[str]] = Field(default_factory=list, description="""Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0.""")
     sync: Optional[TimeSeriesSync] = Field(None, description="""Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of 'sync' are mostly for archival purposes.""")
     
 
@@ -169,6 +166,7 @@ class VoltageClampStimulusSeries(PatchClampSeries):
     """
     Stimulus voltage applied during a voltage clamp recording.
     """
+    name: str = Field(...)
     data: VoltageClampStimulusSeriesData = Field(..., description="""Stimulus voltage applied.""")
     stimulus_description: Optional[str] = Field(None, description="""Protocol/stimulus name for this patch-clamp dataset.""")
     sweep_number: Optional[int] = Field(None, description="""Sweep number, allows to group different PatchClampSeries together.""")
@@ -176,9 +174,9 @@ class VoltageClampStimulusSeries(PatchClampSeries):
     description: Optional[str] = Field(None, description="""Description of the time series.""")
     comments: Optional[str] = Field(None, description="""Human-readable comments about the TimeSeries. This second descriptive field can be used to store additional information, or descriptive information if the primary description field is populated with a computer-readable string.""")
     starting_time: Optional[TimeSeriesStartingTime] = Field(None, description="""Timestamp of the first sample in seconds. When timestamps are uniformly spaced, the timestamp of the first sample can be specified and all subsequent ones calculated from the sampling rate attribute.""")
-    timestamps: Optional[TimeSeriesTimestamps] = Field(None, description="""Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time.""")
-    control: Optional[TimeSeriesControl] = Field(None, description="""Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data.""")
-    control_description: Optional[TimeSeriesControlDescription] = Field(None, description="""Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0.""")
+    timestamps: Optional[List[float]] = Field(default_factory=list, description="""Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time.""")
+    control: Optional[List[int]] = Field(default_factory=list, description="""Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data.""")
+    control_description: Optional[List[str]] = Field(default_factory=list, description="""Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0.""")
     sync: Optional[TimeSeriesSync] = Field(None, description="""Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of 'sync' are mostly for archival purposes.""")
     
 
@@ -186,6 +184,7 @@ class IntracellularElectrode(NWBContainer):
     """
     An intracellular electrode and its metadata.
     """
+    name: str = Field(...)
     cell_id: Optional[str] = Field(None, description="""unique ID of the cell""")
     description: str = Field(..., description="""Description of electrode (e.g.,  whole-cell, sharp, etc.).""")
     filtering: Optional[str] = Field(None, description="""Electrode specific filtering.""")
@@ -200,12 +199,13 @@ class SweepTable(DynamicTable):
     """
     [DEPRECATED] Table used to group different PatchClampSeries. SweepTable is being replaced by IntracellularRecordingsTable and SimultaneousRecordingsTable tables. Additional SequentialRecordingsTable, RepetitionsTable, and ExperimentalConditions tables provide enhanced support for experiment metadata.
     """
+    name: str = Field(...)
     sweep_number: Optional[List[int]] = Field(default_factory=list, description="""Sweep number of the PatchClampSeries in that row.""")
     series: Optional[List[PatchClampSeries]] = Field(default_factory=list, description="""The PatchClampSeries with the sweep number in that row.""")
     series_index: SweepTableSeriesIndex = Field(..., description="""Index for series.""")
     colnames: Optional[str] = Field(None, description="""The names of the columns in this table. This should be used to specify an order to the columns.""")
     description: Optional[str] = Field(None, description="""Description of what is in this dynamic table.""")
-    id: DynamicTableId = Field(..., description="""Array of unique identifiers for the rows of this dynamic table.""")
+    id: List[int] = Field(default_factory=list, description="""Array of unique identifiers for the rows of this dynamic table.""")
     VectorData: Optional[List[VectorData]] = Field(default_factory=list, description="""Vector columns, including index columns, of this dynamic table.""")
     
 
@@ -213,10 +213,11 @@ class IntracellularElectrodesTable(DynamicTable):
     """
     Table for storing intracellular electrode related metadata.
     """
+    name: str = Field(...)
     description: Optional[str] = Field(None, description="""Description of what is in this dynamic table.""")
     electrode: Optional[List[IntracellularElectrode]] = Field(default_factory=list, description="""Column for storing the reference to the intracellular electrode.""")
     colnames: Optional[str] = Field(None, description="""The names of the columns in this table. This should be used to specify an order to the columns.""")
-    id: DynamicTableId = Field(..., description="""Array of unique identifiers for the rows of this dynamic table.""")
+    id: List[int] = Field(default_factory=list, description="""Array of unique identifiers for the rows of this dynamic table.""")
     VectorData: Optional[List[VectorData]] = Field(default_factory=list, description="""Vector columns, including index columns, of this dynamic table.""")
     
 
@@ -224,10 +225,11 @@ class IntracellularStimuliTable(DynamicTable):
     """
     Table for storing intracellular stimulus related metadata.
     """
+    name: str = Field(...)
     description: Optional[str] = Field(None, description="""Description of what is in this dynamic table.""")
     stimulus: IntracellularStimuliTableStimulus = Field(..., description="""Column storing the reference to the recorded stimulus for the recording (rows).""")
     colnames: Optional[str] = Field(None, description="""The names of the columns in this table. This should be used to specify an order to the columns.""")
-    id: DynamicTableId = Field(..., description="""Array of unique identifiers for the rows of this dynamic table.""")
+    id: List[int] = Field(default_factory=list, description="""Array of unique identifiers for the rows of this dynamic table.""")
     VectorData: Optional[List[VectorData]] = Field(default_factory=list, description="""Vector columns, including index columns, of this dynamic table.""")
     
 
@@ -235,10 +237,11 @@ class IntracellularResponsesTable(DynamicTable):
     """
     Table for storing intracellular response related metadata.
     """
+    name: str = Field(...)
     description: Optional[str] = Field(None, description="""Description of what is in this dynamic table.""")
     response: IntracellularResponsesTableResponse = Field(..., description="""Column storing the reference to the recorded response for the recording (rows)""")
     colnames: Optional[str] = Field(None, description="""The names of the columns in this table. This should be used to specify an order to the columns.""")
-    id: DynamicTableId = Field(..., description="""Array of unique identifiers for the rows of this dynamic table.""")
+    id: List[int] = Field(default_factory=list, description="""Array of unique identifiers for the rows of this dynamic table.""")
     VectorData: Optional[List[VectorData]] = Field(default_factory=list, description="""Vector columns, including index columns, of this dynamic table.""")
     
 
@@ -246,14 +249,15 @@ class IntracellularRecordingsTable(AlignedDynamicTable):
     """
     A table to group together a stimulus and response from a single electrode and a single simultaneous recording. Each row in the table represents a single recording consisting typically of a stimulus and a corresponding response. In some cases, however, only a stimulus or a response is recorded as part of an experiment. In this case, both the stimulus and response will point to the same TimeSeries while the idx_start and count of the invalid column will be set to -1, thus, indicating that no values have been recorded for the stimulus or response, respectively. Note, a recording MUST contain at least a stimulus or a response. Typically the stimulus and response are PatchClampSeries. However, the use of AD/DA channels that are not associated to an electrode is also common in intracellular electrophysiology, in which case other TimeSeries may be used.
     """
+    name: str = Field("intracellular_recordings", const=True)
     description: Optional[str] = Field(None, description="""Description of the contents of this table. Inherited from AlignedDynamicTable and overwritten here to fix the value of the attribute.""")
-    electrodes: IntracellularRecordingsTableElectrodes = Field(..., description="""Table for storing intracellular electrode related metadata.""")
-    stimuli: IntracellularRecordingsTableStimuli = Field(..., description="""Table for storing intracellular stimulus related metadata.""")
-    responses: IntracellularRecordingsTableResponses = Field(..., description="""Table for storing intracellular response related metadata.""")
+    electrodes: IntracellularElectrodesTable = Field(..., description="""Table for storing intracellular electrode related metadata.""")
+    stimuli: IntracellularStimuliTable = Field(..., description="""Table for storing intracellular stimulus related metadata.""")
+    responses: IntracellularResponsesTable = Field(..., description="""Table for storing intracellular response related metadata.""")
     categories: Optional[str] = Field(None, description="""The names of the categories in this AlignedDynamicTable. Each category is represented by one DynamicTable stored in the parent group. This attribute should be used to specify an order of categories and the category names must match the names of the corresponding DynamicTable in the group.""")
-    DynamicTable: Optional[List[DynamicTable]] = Field(default_factory=list, description="""A DynamicTable representing a particular category for columns in the AlignedDynamicTable parent container. The table MUST be aligned with (i.e., have the same number of rows) as all other DynamicTables stored in the AlignedDynamicTable parent container. The name of the category is given by the name of the DynamicTable and its description by the description attribute of the DynamicTable.""")
+    dynamic_table: Optional[List[DynamicTable]] = Field(default_factory=list, description="""A DynamicTable representing a particular category for columns in the AlignedDynamicTable parent container. The table MUST be aligned with (i.e., have the same number of rows) as all other DynamicTables stored in the AlignedDynamicTable parent container. The name of the category is given by the name of the DynamicTable and its description by the description attribute of the DynamicTable.""")
     colnames: Optional[str] = Field(None, description="""The names of the columns in this table. This should be used to specify an order to the columns.""")
-    id: DynamicTableId = Field(..., description="""Array of unique identifiers for the rows of this dynamic table.""")
+    id: List[int] = Field(default_factory=list, description="""Array of unique identifiers for the rows of this dynamic table.""")
     VectorData: Optional[List[VectorData]] = Field(default_factory=list, description="""Vector columns, including index columns, of this dynamic table.""")
     
 
@@ -261,11 +265,12 @@ class SimultaneousRecordingsTable(DynamicTable):
     """
     A table for grouping different intracellular recordings from the IntracellularRecordingsTable table together that were recorded simultaneously from different electrodes.
     """
+    name: str = Field("simultaneous_recordings", const=True)
     recordings: SimultaneousRecordingsTableRecordings = Field(..., description="""A reference to one or more rows in the IntracellularRecordingsTable table.""")
     recordings_index: SimultaneousRecordingsTableRecordingsIndex = Field(..., description="""Index dataset for the recordings column.""")
     colnames: Optional[str] = Field(None, description="""The names of the columns in this table. This should be used to specify an order to the columns.""")
     description: Optional[str] = Field(None, description="""Description of what is in this dynamic table.""")
-    id: DynamicTableId = Field(..., description="""Array of unique identifiers for the rows of this dynamic table.""")
+    id: List[int] = Field(default_factory=list, description="""Array of unique identifiers for the rows of this dynamic table.""")
     VectorData: Optional[List[VectorData]] = Field(default_factory=list, description="""Vector columns, including index columns, of this dynamic table.""")
     
 
@@ -273,12 +278,13 @@ class SequentialRecordingsTable(DynamicTable):
     """
     A table for grouping different sequential recordings from the SimultaneousRecordingsTable table together. This is typically used to group together sequential recordings where a sequence of stimuli of the same type with varying parameters have been presented in a sequence.
     """
+    name: str = Field("sequential_recordings", const=True)
     simultaneous_recordings: SequentialRecordingsTableSimultaneousRecordings = Field(..., description="""A reference to one or more rows in the SimultaneousRecordingsTable table.""")
     simultaneous_recordings_index: SequentialRecordingsTableSimultaneousRecordingsIndex = Field(..., description="""Index dataset for the simultaneous_recordings column.""")
     stimulus_type: Optional[List[str]] = Field(default_factory=list, description="""The type of stimulus used for the sequential recording.""")
     colnames: Optional[str] = Field(None, description="""The names of the columns in this table. This should be used to specify an order to the columns.""")
     description: Optional[str] = Field(None, description="""Description of what is in this dynamic table.""")
-    id: DynamicTableId = Field(..., description="""Array of unique identifiers for the rows of this dynamic table.""")
+    id: List[int] = Field(default_factory=list, description="""Array of unique identifiers for the rows of this dynamic table.""")
     VectorData: Optional[List[VectorData]] = Field(default_factory=list, description="""Vector columns, including index columns, of this dynamic table.""")
     
 
@@ -286,11 +292,12 @@ class RepetitionsTable(DynamicTable):
     """
     A table for grouping different sequential intracellular recordings together. With each SequentialRecording typically representing a particular type of stimulus, the RepetitionsTable table is typically used to group sets of stimuli applied in sequence.
     """
+    name: str = Field("repetitions", const=True)
     sequential_recordings: RepetitionsTableSequentialRecordings = Field(..., description="""A reference to one or more rows in the SequentialRecordingsTable table.""")
     sequential_recordings_index: RepetitionsTableSequentialRecordingsIndex = Field(..., description="""Index dataset for the sequential_recordings column.""")
     colnames: Optional[str] = Field(None, description="""The names of the columns in this table. This should be used to specify an order to the columns.""")
     description: Optional[str] = Field(None, description="""Description of what is in this dynamic table.""")
-    id: DynamicTableId = Field(..., description="""Array of unique identifiers for the rows of this dynamic table.""")
+    id: List[int] = Field(default_factory=list, description="""Array of unique identifiers for the rows of this dynamic table.""")
     VectorData: Optional[List[VectorData]] = Field(default_factory=list, description="""Vector columns, including index columns, of this dynamic table.""")
     
 
@@ -298,30 +305,32 @@ class ExperimentalConditionsTable(DynamicTable):
     """
     A table for grouping different intracellular recording repetitions together that belong to the same experimental condition.
     """
+    name: str = Field("experimental_conditions", const=True)
     repetitions: ExperimentalConditionsTableRepetitions = Field(..., description="""A reference to one or more rows in the RepetitionsTable table.""")
     repetitions_index: ExperimentalConditionsTableRepetitionsIndex = Field(..., description="""Index dataset for the repetitions column.""")
     colnames: Optional[str] = Field(None, description="""The names of the columns in this table. This should be used to specify an order to the columns.""")
     description: Optional[str] = Field(None, description="""Description of what is in this dynamic table.""")
-    id: DynamicTableId = Field(..., description="""Array of unique identifiers for the rows of this dynamic table.""")
+    id: List[int] = Field(default_factory=list, description="""Array of unique identifiers for the rows of this dynamic table.""")
     VectorData: Optional[List[VectorData]] = Field(default_factory=list, description="""Vector columns, including index columns, of this dynamic table.""")
     
 
 
-# Update forward refs
-# see https://pydantic-docs.helpmanual.io/usage/postponed_annotations/
-PatchClampSeries.update_forward_refs()
-CurrentClampSeries.update_forward_refs()
-IZeroClampSeries.update_forward_refs()
-CurrentClampStimulusSeries.update_forward_refs()
-VoltageClampSeries.update_forward_refs()
-VoltageClampStimulusSeries.update_forward_refs()
-IntracellularElectrode.update_forward_refs()
-SweepTable.update_forward_refs()
-IntracellularElectrodesTable.update_forward_refs()
-IntracellularStimuliTable.update_forward_refs()
-IntracellularResponsesTable.update_forward_refs()
-IntracellularRecordingsTable.update_forward_refs()
-SimultaneousRecordingsTable.update_forward_refs()
-SequentialRecordingsTable.update_forward_refs()
-RepetitionsTable.update_forward_refs()
-ExperimentalConditionsTable.update_forward_refs()
+# Model rebuild
+# see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
+PatchClampSeries.model_rebuild()
+CurrentClampSeries.model_rebuild()
+IZeroClampSeries.model_rebuild()
+CurrentClampStimulusSeries.model_rebuild()
+VoltageClampSeries.model_rebuild()
+VoltageClampStimulusSeries.model_rebuild()
+IntracellularElectrode.model_rebuild()
+SweepTable.model_rebuild()
+IntracellularElectrodesTable.model_rebuild()
+IntracellularStimuliTable.model_rebuild()
+IntracellularResponsesTable.model_rebuild()
+IntracellularRecordingsTable.model_rebuild()
+SimultaneousRecordingsTable.model_rebuild()
+SequentialRecordingsTable.model_rebuild()
+RepetitionsTable.model_rebuild()
+ExperimentalConditionsTable.model_rebuild()
+    

nwb_linkml/models/core_nwb_icephys_include.py

@@ -16,49 +16,35 @@ from .hdmf_common_table import (
     VectorIndex
 )
 
-from .core_nwb_base import (
-    TimeSeriesReferenceVectorData
+from .core_nwb_icephys import (
+    SequentialRecordingsTable,
+    RepetitionsTable,
+    SimultaneousRecordingsTable,
+    IntracellularRecordingsTable
 )
 
-from .core_nwb_icephys import (
-    SimultaneousRecordingsTable,
-    IntracellularElectrodesTable,
-    IntracellularResponsesTable,
-    SequentialRecordingsTable,
-    IntracellularRecordingsTable,
-    IntracellularStimuliTable,
-    RepetitionsTable
+from .core_nwb_base import (
+    TimeSeriesReferenceVectorData
 )
 
 
 metamodel_version = "None"
 version = "None"
 
-class WeakRefShimBaseModel(BaseModel):
-   __slots__ = '__weakref__'
-
-class ConfiguredBaseModel(WeakRefShimBaseModel,
+class ConfiguredBaseModel(BaseModel,
                 validate_assignment = True,
-                validate_all = True,
-                underscore_attrs_are_private = True,
+                validate_default = True,
                 extra = 'forbid',
                 arbitrary_types_allowed = True,
                 use_enum_values = True):
     pass
 
 
-class PatchClampSeriesData(ConfiguredBaseModel):
-    """
-    Recorded voltage or current.
-    """
-    unit: Optional[str] = Field(None, description="""Base unit of measurement for working with the data. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion' and add 'offset'.""")
-    data: List[float] = Field(default_factory=list, description="""Recorded voltage or current.""")
-    
-
 class CurrentClampSeriesData(ConfiguredBaseModel):
     """
     Recorded voltage.
     """
+    name: str = Field("data", const=True)
     unit: Optional[str] = Field(None, description="""Base unit of measurement for working with the data. which is fixed to 'volts'. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion' and add 'offset'.""")
     
 
@@ -66,6 +52,7 @@ class CurrentClampStimulusSeriesData(ConfiguredBaseModel):
     """
     Stimulus current applied.
     """
+    name: str = Field("data", const=True)
     unit: Optional[str] = Field(None, description="""Base unit of measurement for working with the data. which is fixed to 'amperes'. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion' and add 'offset'.""")
     
 
@@ -73,6 +60,7 @@ class VoltageClampSeriesData(ConfiguredBaseModel):
     """
     Recorded current.
     """
+    name: str = Field("data", const=True)
     unit: Optional[str] = Field(None, description="""Base unit of measurement for working with the data. which is fixed to 'amperes'. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion' and add 'offset'.""")
     
 
@@ -80,6 +68,7 @@ class VoltageClampSeriesCapacitanceFast(ConfiguredBaseModel):
     """
     Fast capacitance, in farads.
     """
+    name: str = Field("capacitance_fast", const=True)
     unit: Optional[str] = Field(None, description="""Unit of measurement for capacitance_fast, which is fixed to 'farads'.""")
     
 
@@ -87,6 +76,7 @@ class VoltageClampSeriesCapacitanceSlow(ConfiguredBaseModel):
     """
     Slow capacitance, in farads.
     """
+    name: str = Field("capacitance_slow", const=True)
     unit: Optional[str] = Field(None, description="""Unit of measurement for capacitance_fast, which is fixed to 'farads'.""")
     
 
@@ -94,6 +84,7 @@ class VoltageClampSeriesResistanceCompBandwidth(ConfiguredBaseModel):
     """
     Resistance compensation bandwidth, in hertz.
     """
+    name: str = Field("resistance_comp_bandwidth", const=True)
     unit: Optional[str] = Field(None, description="""Unit of measurement for resistance_comp_bandwidth, which is fixed to 'hertz'.""")
     
 
@@ -101,6 +92,7 @@ class VoltageClampSeriesResistanceCompCorrection(ConfiguredBaseModel):
     """
     Resistance compensation correction, in percent.
     """
+    name: str = Field("resistance_comp_correction", const=True)
     unit: Optional[str] = Field(None, description="""Unit of measurement for resistance_comp_correction, which is fixed to 'percent'.""")
     
 
@@ -108,6 +100,7 @@ class VoltageClampSeriesResistanceCompPrediction(ConfiguredBaseModel):
     """
     Resistance compensation prediction, in percent.
     """
+    name: str = Field("resistance_comp_prediction", const=True)
     unit: Optional[str] = Field(None, description="""Unit of measurement for resistance_comp_prediction, which is fixed to 'percent'.""")
     
 
@@ -115,6 +108,7 @@ class VoltageClampSeriesWholeCellCapacitanceComp(ConfiguredBaseModel):
     """
     Whole cell capacitance compensation, in farads.
     """
+    name: str = Field("whole_cell_capacitance_comp", const=True)
     unit: Optional[str] = Field(None, description="""Unit of measurement for whole_cell_capacitance_comp, which is fixed to 'farads'.""")
     
 
@@ -122,6 +116,7 @@ class VoltageClampSeriesWholeCellSeriesResistanceComp(ConfiguredBaseModel):
     """
     Whole cell series resistance compensation, in ohms.
     """
+    name: str = Field("whole_cell_series_resistance_comp", const=True)
     unit: Optional[str] = Field(None, description="""Unit of measurement for whole_cell_series_resistance_comp, which is fixed to 'ohms'.""")
     
 
@@ -129,6 +124,7 @@ class VoltageClampStimulusSeriesData(ConfiguredBaseModel):
     """
     Stimulus voltage applied.
     """
+    name: str = Field("data", const=True)
     unit: Optional[str] = Field(None, description="""Base unit of measurement for working with the data. which is fixed to 'volts'. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion' and add 'offset'.""")
     
 
@@ -136,158 +132,188 @@ class SweepTableSeriesIndex(VectorIndex):
     """
     Index for series.
     """
+    name: str = Field("series_index", const=True)
     target: Optional[VectorData] = Field(None, description="""Reference to the target dataset that this index applies to.""")
     description: Optional[str] = Field(None, description="""Description of what these vectors represent.""")
-    array: Optional[NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], ]] = Field(None)
+    array: Optional[Union[
+        NDArray[Shape["* dim0"], Any],
+        NDArray[Shape["* dim0, * dim1"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], Any]
+    ]] = Field(None)
     
 
 class IntracellularStimuliTableStimulus(TimeSeriesReferenceVectorData):
     """
     Column storing the reference to the recorded stimulus for the recording (rows).
     """
+    name: str = Field("stimulus", const=True)
     description: Optional[str] = Field(None, description="""Description of what these vectors represent.""")
-    array: Optional[NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], ]] = Field(None)
+    array: Optional[Union[
+        NDArray[Shape["* dim0"], Any],
+        NDArray[Shape["* dim0, * dim1"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], Any]
+    ]] = Field(None)
     
 
 class IntracellularResponsesTableResponse(TimeSeriesReferenceVectorData):
     """
     Column storing the reference to the recorded response for the recording (rows)
     """
+    name: str = Field("response", const=True)
     description: Optional[str] = Field(None, description="""Description of what these vectors represent.""")
-    array: Optional[NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], ]] = Field(None)
-    
-
-class IntracellularRecordingsTableElectrodes(IntracellularElectrodesTable):
-    """
-    Table for storing intracellular electrode related metadata.
-    """
-    description: Optional[str] = Field(None, description="""Description of what is in this dynamic table.""")
-    electrode: Optional[List[IntracellularElectrode]] = Field(default_factory=list, description="""Column for storing the reference to the intracellular electrode.""")
-    colnames: Optional[str] = Field(None, description="""The names of the columns in this table. This should be used to specify an order to the columns.""")
-    id: DynamicTableId = Field(..., description="""Array of unique identifiers for the rows of this dynamic table.""")
-    VectorData: Optional[List[VectorData]] = Field(default_factory=list, description="""Vector columns, including index columns, of this dynamic table.""")
-    
-
-class IntracellularRecordingsTableStimuli(IntracellularStimuliTable):
-    """
-    Table for storing intracellular stimulus related metadata.
-    """
-    description: Optional[str] = Field(None, description="""Description of what is in this dynamic table.""")
-    stimulus: IntracellularStimuliTableStimulus = Field(..., description="""Column storing the reference to the recorded stimulus for the recording (rows).""")
-    colnames: Optional[str] = Field(None, description="""The names of the columns in this table. This should be used to specify an order to the columns.""")
-    id: DynamicTableId = Field(..., description="""Array of unique identifiers for the rows of this dynamic table.""")
-    VectorData: Optional[List[VectorData]] = Field(default_factory=list, description="""Vector columns, including index columns, of this dynamic table.""")
-    
-
-class IntracellularRecordingsTableResponses(IntracellularResponsesTable):
-    """
-    Table for storing intracellular response related metadata.
-    """
-    description: Optional[str] = Field(None, description="""Description of what is in this dynamic table.""")
-    response: IntracellularResponsesTableResponse = Field(..., description="""Column storing the reference to the recorded response for the recording (rows)""")
-    colnames: Optional[str] = Field(None, description="""The names of the columns in this table. This should be used to specify an order to the columns.""")
-    id: DynamicTableId = Field(..., description="""Array of unique identifiers for the rows of this dynamic table.""")
-    VectorData: Optional[List[VectorData]] = Field(default_factory=list, description="""Vector columns, including index columns, of this dynamic table.""")
+    array: Optional[Union[
+        NDArray[Shape["* dim0"], Any],
+        NDArray[Shape["* dim0, * dim1"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], Any]
+    ]] = Field(None)
     
 
 class SimultaneousRecordingsTableRecordings(DynamicTableRegion):
     """
     A reference to one or more rows in the IntracellularRecordingsTable table.
     """
+    name: str = Field("recordings", const=True)
     table: Optional[IntracellularRecordingsTable] = Field(None, description="""Reference to the IntracellularRecordingsTable table that this table region applies to. This specializes the attribute inherited from DynamicTableRegion to fix the type of table that can be referenced here.""")
     description: Optional[str] = Field(None, description="""Description of what this table region points to.""")
-    array: Optional[NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], ]] = Field(None)
+    array: Optional[Union[
+        NDArray[Shape["* dim0"], Any],
+        NDArray[Shape["* dim0, * dim1"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], Any]
+    ]] = Field(None)
     
 
 class SimultaneousRecordingsTableRecordingsIndex(VectorIndex):
     """
     Index dataset for the recordings column.
     """
+    name: str = Field("recordings_index", const=True)
     target: Optional[VectorData] = Field(None, description="""Reference to the target dataset that this index applies to.""")
     description: Optional[str] = Field(None, description="""Description of what these vectors represent.""")
-    array: Optional[NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], ]] = Field(None)
+    array: Optional[Union[
+        NDArray[Shape["* dim0"], Any],
+        NDArray[Shape["* dim0, * dim1"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], Any]
+    ]] = Field(None)
     
 
 class SequentialRecordingsTableSimultaneousRecordings(DynamicTableRegion):
     """
     A reference to one or more rows in the SimultaneousRecordingsTable table.
     """
+    name: str = Field("simultaneous_recordings", const=True)
     table: Optional[SimultaneousRecordingsTable] = Field(None, description="""Reference to the SimultaneousRecordingsTable table that this table region applies to. This specializes the attribute inherited from DynamicTableRegion to fix the type of table that can be referenced here.""")
     description: Optional[str] = Field(None, description="""Description of what this table region points to.""")
-    array: Optional[NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], ]] = Field(None)
+    array: Optional[Union[
+        NDArray[Shape["* dim0"], Any],
+        NDArray[Shape["* dim0, * dim1"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], Any]
+    ]] = Field(None)
     
 
 class SequentialRecordingsTableSimultaneousRecordingsIndex(VectorIndex):
     """
     Index dataset for the simultaneous_recordings column.
     """
+    name: str = Field("simultaneous_recordings_index", const=True)
     target: Optional[VectorData] = Field(None, description="""Reference to the target dataset that this index applies to.""")
     description: Optional[str] = Field(None, description="""Description of what these vectors represent.""")
-    array: Optional[NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], ]] = Field(None)
+    array: Optional[Union[
+        NDArray[Shape["* dim0"], Any],
+        NDArray[Shape["* dim0, * dim1"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], Any]
+    ]] = Field(None)
     
 
 class RepetitionsTableSequentialRecordings(DynamicTableRegion):
     """
     A reference to one or more rows in the SequentialRecordingsTable table.
     """
+    name: str = Field("sequential_recordings", const=True)
     table: Optional[SequentialRecordingsTable] = Field(None, description="""Reference to the SequentialRecordingsTable table that this table region applies to. This specializes the attribute inherited from DynamicTableRegion to fix the type of table that can be referenced here.""")
     description: Optional[str] = Field(None, description="""Description of what this table region points to.""")
-    array: Optional[NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], ]] = Field(None)
+    array: Optional[Union[
+        NDArray[Shape["* dim0"], Any],
+        NDArray[Shape["* dim0, * dim1"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], Any]
+    ]] = Field(None)
     
 
 class RepetitionsTableSequentialRecordingsIndex(VectorIndex):
     """
     Index dataset for the sequential_recordings column.
     """
+    name: str = Field("sequential_recordings_index", const=True)
     target: Optional[VectorData] = Field(None, description="""Reference to the target dataset that this index applies to.""")
     description: Optional[str] = Field(None, description="""Description of what these vectors represent.""")
-    array: Optional[NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], ]] = Field(None)
+    array: Optional[Union[
+        NDArray[Shape["* dim0"], Any],
+        NDArray[Shape["* dim0, * dim1"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], Any]
+    ]] = Field(None)
     
 
 class ExperimentalConditionsTableRepetitions(DynamicTableRegion):
     """
     A reference to one or more rows in the RepetitionsTable table.
     """
+    name: str = Field("repetitions", const=True)
     table: Optional[RepetitionsTable] = Field(None, description="""Reference to the RepetitionsTable table that this table region applies to. This specializes the attribute inherited from DynamicTableRegion to fix the type of table that can be referenced here.""")
     description: Optional[str] = Field(None, description="""Description of what this table region points to.""")
-    array: Optional[NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], ]] = Field(None)
+    array: Optional[Union[
+        NDArray[Shape["* dim0"], Any],
+        NDArray[Shape["* dim0, * dim1"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], Any]
+    ]] = Field(None)
     
 
 class ExperimentalConditionsTableRepetitionsIndex(VectorIndex):
     """
     Index dataset for the repetitions column.
     """
+    name: str = Field("repetitions_index", const=True)
     target: Optional[VectorData] = Field(None, description="""Reference to the target dataset that this index applies to.""")
     description: Optional[str] = Field(None, description="""Description of what these vectors represent.""")
-    array: Optional[NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], ]] = Field(None)
+    array: Optional[Union[
+        NDArray[Shape["* dim0"], Any],
+        NDArray[Shape["* dim0, * dim1"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], Any]
+    ]] = Field(None)
     
 
 
-# Update forward refs
-# see https://pydantic-docs.helpmanual.io/usage/postponed_annotations/
-PatchClampSeriesData.update_forward_refs()
-CurrentClampSeriesData.update_forward_refs()
-CurrentClampStimulusSeriesData.update_forward_refs()
-VoltageClampSeriesData.update_forward_refs()
-VoltageClampSeriesCapacitanceFast.update_forward_refs()
-VoltageClampSeriesCapacitanceSlow.update_forward_refs()
-VoltageClampSeriesResistanceCompBandwidth.update_forward_refs()
-VoltageClampSeriesResistanceCompCorrection.update_forward_refs()
-VoltageClampSeriesResistanceCompPrediction.update_forward_refs()
-VoltageClampSeriesWholeCellCapacitanceComp.update_forward_refs()
-VoltageClampSeriesWholeCellSeriesResistanceComp.update_forward_refs()
-VoltageClampStimulusSeriesData.update_forward_refs()
-SweepTableSeriesIndex.update_forward_refs()
-IntracellularStimuliTableStimulus.update_forward_refs()
-IntracellularResponsesTableResponse.update_forward_refs()
-IntracellularRecordingsTableElectrodes.update_forward_refs()
-IntracellularRecordingsTableStimuli.update_forward_refs()
-IntracellularRecordingsTableResponses.update_forward_refs()
-SimultaneousRecordingsTableRecordings.update_forward_refs()
-SimultaneousRecordingsTableRecordingsIndex.update_forward_refs()
-SequentialRecordingsTableSimultaneousRecordings.update_forward_refs()
-SequentialRecordingsTableSimultaneousRecordingsIndex.update_forward_refs()
-RepetitionsTableSequentialRecordings.update_forward_refs()
-RepetitionsTableSequentialRecordingsIndex.update_forward_refs()
-ExperimentalConditionsTableRepetitions.update_forward_refs()
-ExperimentalConditionsTableRepetitionsIndex.update_forward_refs()
+# Model rebuild
+# see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
+CurrentClampSeriesData.model_rebuild()
+CurrentClampStimulusSeriesData.model_rebuild()
+VoltageClampSeriesData.model_rebuild()
+VoltageClampSeriesCapacitanceFast.model_rebuild()
+VoltageClampSeriesCapacitanceSlow.model_rebuild()
+VoltageClampSeriesResistanceCompBandwidth.model_rebuild()
+VoltageClampSeriesResistanceCompCorrection.model_rebuild()
+VoltageClampSeriesResistanceCompPrediction.model_rebuild()
+VoltageClampSeriesWholeCellCapacitanceComp.model_rebuild()
+VoltageClampSeriesWholeCellSeriesResistanceComp.model_rebuild()
+VoltageClampStimulusSeriesData.model_rebuild()
+SweepTableSeriesIndex.model_rebuild()
+IntracellularStimuliTableStimulus.model_rebuild()
+IntracellularResponsesTableResponse.model_rebuild()
+SimultaneousRecordingsTableRecordings.model_rebuild()
+SimultaneousRecordingsTableRecordingsIndex.model_rebuild()
+SequentialRecordingsTableSimultaneousRecordings.model_rebuild()
+SequentialRecordingsTableSimultaneousRecordingsIndex.model_rebuild()
+RepetitionsTableSequentialRecordings.model_rebuild()
+RepetitionsTableSequentialRecordingsIndex.model_rebuild()
+ExperimentalConditionsTableRepetitions.model_rebuild()
+ExperimentalConditionsTableRepetitionsIndex.model_rebuild()
+    

nwb_linkml/models/core_nwb_image.py

@@ -11,44 +11,38 @@ else:
     from typing_extensions import Literal
 
 
-# from .core_nwb_image_include import (
-#     ImageSeriesData,
-#     OpticalSeriesFieldOfView,
-#     RGBAImageArray,
-#     IndexSeriesData,
-#     ImageSeriesDimension,
-#     OpticalSeriesData,
-#     ImageSeriesExternalFile,
-#     GrayscaleImageArray,
-#     RGBImageArray
-# )
-
 from .core_nwb_base import (
-    Image,
-    TimeSeries
+    TimeSeries,
+    Image
+)
+
+from .core_nwb_image_include import (
+    ImageSeriesData,
+    RGBAImageArray,
+    GrayscaleImageArray,
+    RGBImageArray,
+    OpticalSeriesFieldOfView,
+    OpticalSeriesData
 )
 
 
 metamodel_version = "None"
 version = "None"
 
-class WeakRefShimBaseModel(BaseModel):
-   __slots__ = '__weakref__'
-
-class ConfiguredBaseModel(WeakRefShimBaseModel,
+class ConfiguredBaseModel(BaseModel,
                 validate_assignment = True,
-                validate_all = True,
-                underscore_attrs_are_private = True,
+                validate_default = True,
                 extra = 'forbid',
                 arbitrary_types_allowed = True,
                 use_enum_values = True):
     pass
 
 
-class GrayscaleImage(ConfiguredBaseModel):
+class GrayscaleImage(Image):
     """
     A grayscale image.
     """
+    name: str = Field(...)
     array: Optional[NDArray[Shape["* x, * y"], Number]] = Field(None)
     resolution: Optional[float] = Field(None, description="""Pixel resolution of the image, in pixels per centimeter.""")
     description: Optional[str] = Field(None, description="""Description of the image.""")
@@ -58,6 +52,7 @@ class RGBImage(Image):
     """
     A color image.
     """
+    name: str = Field(...)
     array: Optional[NDArray[Shape["* x, * y, 3 r_g_b"], Number]] = Field(None)
     resolution: Optional[float] = Field(None, description="""Pixel resolution of the image, in pixels per centimeter.""")
     description: Optional[str] = Field(None, description="""Description of the image.""")
@@ -67,86 +62,92 @@ class RGBAImage(Image):
     """
     A color image with transparency.
     """
+    name: str = Field(...)
     array: Optional[NDArray[Shape["* x, * y, 4 r_g_b_a"], Number]] = Field(None)
     resolution: Optional[float] = Field(None, description="""Pixel resolution of the image, in pixels per centimeter.""")
     description: Optional[str] = Field(None, description="""Description of the image.""")
     
-#
-# class ImageSeries(TimeSeries):
-#     """
-#     General image data that is common between acquisition and stimulus time series. Sometimes the image data is stored in the file in a raw format while other times it will be stored as a series of external image files in the host file system. The data field will either be binary data, if the data is stored in the NWB file, or empty, if the data is stored in an external image stack. [frame][x][y] or [frame][x][y][z].
-#     """
-#     data: ImageSeriesData = Field(..., description="""Binary data representing images across frames. If data are stored in an external file, this should be an empty 3D array.""")
-#     dimension: Optional[ImageSeriesDimension] = Field(None, description="""Number of pixels on x, y, (and z) axes.""")
-#     external_file: Optional[ImageSeriesExternalFile] = Field(None, description="""Paths to one or more external file(s). The field is only present if format='external'. This is only relevant if the image series is stored in the file system as one or more image file(s). This field should NOT be used if the image is stored in another NWB file and that file is linked to this file.""")
-#     format: Optional[str] = Field(None, description="""Format of image. If this is 'external', then the attribute 'external_file' contains the path information to the image files. If this is 'raw', then the raw (single-channel) binary data is stored in the 'data' dataset. If this attribute is not present, then the default format='raw' case is assumed.""")
-#     description: Optional[str] = Field(None, description="""Description of the time series.""")
-#     comments: Optional[str] = Field(None, description="""Human-readable comments about the TimeSeries. This second descriptive field can be used to store additional information, or descriptive information if the primary description field is populated with a computer-readable string.""")
-#     starting_time: Optional[TimeSeriesStartingTime] = Field(None, description="""Timestamp of the first sample in seconds. When timestamps are uniformly spaced, the timestamp of the first sample can be specified and all subsequent ones calculated from the sampling rate attribute.""")
-#     timestamps: Optional[TimeSeriesTimestamps] = Field(None, description="""Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time.""")
-#     control: Optional[TimeSeriesControl] = Field(None, description="""Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data.""")
-#     control_description: Optional[TimeSeriesControlDescription] = Field(None, description="""Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0.""")
-#     sync: Optional[TimeSeriesSync] = Field(None, description="""Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of 'sync' are mostly for archival purposes.""")
-#
-#
-# class ImageMaskSeries(ImageSeries):
-#     """
-#     An alpha mask that is applied to a presented visual stimulus. The 'data' array contains an array of mask values that are applied to the displayed image. Mask values are stored as RGBA. Mask can vary with time. The timestamps array indicates the starting time of a mask, and that mask pattern continues until it's explicitly changed.
-#     """
-#     data: ImageSeriesData = Field(..., description="""Binary data representing images across frames. If data are stored in an external file, this should be an empty 3D array.""")
-#     dimension: Optional[ImageSeriesDimension] = Field(None, description="""Number of pixels on x, y, (and z) axes.""")
-#     external_file: Optional[ImageSeriesExternalFile] = Field(None, description="""Paths to one or more external file(s). The field is only present if format='external'. This is only relevant if the image series is stored in the file system as one or more image file(s). This field should NOT be used if the image is stored in another NWB file and that file is linked to this file.""")
-#     format: Optional[str] = Field(None, description="""Format of image. If this is 'external', then the attribute 'external_file' contains the path information to the image files. If this is 'raw', then the raw (single-channel) binary data is stored in the 'data' dataset. If this attribute is not present, then the default format='raw' case is assumed.""")
-#     description: Optional[str] = Field(None, description="""Description of the time series.""")
-#     comments: Optional[str] = Field(None, description="""Human-readable comments about the TimeSeries. This second descriptive field can be used to store additional information, or descriptive information if the primary description field is populated with a computer-readable string.""")
-#     starting_time: Optional[TimeSeriesStartingTime] = Field(None, description="""Timestamp of the first sample in seconds. When timestamps are uniformly spaced, the timestamp of the first sample can be specified and all subsequent ones calculated from the sampling rate attribute.""")
-#     timestamps: Optional[TimeSeriesTimestamps] = Field(None, description="""Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time.""")
-#     control: Optional[TimeSeriesControl] = Field(None, description="""Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data.""")
-#     control_description: Optional[TimeSeriesControlDescription] = Field(None, description="""Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0.""")
-#     sync: Optional[TimeSeriesSync] = Field(None, description="""Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of 'sync' are mostly for archival purposes.""")
-#
-#
-# class OpticalSeries(ImageSeries):
-#     """
-#     Image data that is presented or recorded. A stimulus template movie will be stored only as an image. When the image is presented as stimulus, additional data is required, such as field of view (e.g., how much of the visual field the image covers, or how what is the area of the target being imaged). If the OpticalSeries represents acquired imaging data, orientation is also important.
-#     """
-#     distance: Optional[float] = Field(None, description="""Distance from camera/monitor to target/eye.""")
-#     field_of_view: Optional[OpticalSeriesFieldOfView] = Field(None, description="""Width, height and depth of image, or imaged area, in meters.""")
-#     data: OpticalSeriesData = Field(..., description="""Images presented to subject, either grayscale or RGB""")
-#     orientation: Optional[str] = Field(None, description="""Description of image relative to some reference frame (e.g., which way is up). Must also specify frame of reference.""")
-#     dimension: Optional[ImageSeriesDimension] = Field(None, description="""Number of pixels on x, y, (and z) axes.""")
-#     external_file: Optional[ImageSeriesExternalFile] = Field(None, description="""Paths to one or more external file(s). The field is only present if format='external'. This is only relevant if the image series is stored in the file system as one or more image file(s). This field should NOT be used if the image is stored in another NWB file and that file is linked to this file.""")
-#     format: Optional[str] = Field(None, description="""Format of image. If this is 'external', then the attribute 'external_file' contains the path information to the image files. If this is 'raw', then the raw (single-channel) binary data is stored in the 'data' dataset. If this attribute is not present, then the default format='raw' case is assumed.""")
-#     description: Optional[str] = Field(None, description="""Description of the time series.""")
-#     comments: Optional[str] = Field(None, description="""Human-readable comments about the TimeSeries. This second descriptive field can be used to store additional information, or descriptive information if the primary description field is populated with a computer-readable string.""")
-#     starting_time: Optional[TimeSeriesStartingTime] = Field(None, description="""Timestamp of the first sample in seconds. When timestamps are uniformly spaced, the timestamp of the first sample can be specified and all subsequent ones calculated from the sampling rate attribute.""")
-#     timestamps: Optional[TimeSeriesTimestamps] = Field(None, description="""Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time.""")
-#     control: Optional[TimeSeriesControl] = Field(None, description="""Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data.""")
-#     control_description: Optional[TimeSeriesControlDescription] = Field(None, description="""Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0.""")
-#     sync: Optional[TimeSeriesSync] = Field(None, description="""Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of 'sync' are mostly for archival purposes.""")
-#
-#
-# class IndexSeries(TimeSeries):
-#     """
-#     Stores indices to image frames stored in an ImageSeries. The purpose of the IndexSeries is to allow a static image stack to be stored in an Images object, and the images in the stack to be referenced out-of-order. This can be for the display of individual images, or of movie segments (as a movie is simply a series of images). The data field stores the index of the frame in the referenced Images object, and the timestamps array indicates when that image was displayed.
-#     """
-#     data: IndexSeriesData = Field(..., description="""Index of the image (using zero-indexing) in the linked Images object.""")
-#     description: Optional[str] = Field(None, description="""Description of the time series.""")
-#     comments: Optional[str] = Field(None, description="""Human-readable comments about the TimeSeries. This second descriptive field can be used to store additional information, or descriptive information if the primary description field is populated with a computer-readable string.""")
-#     starting_time: Optional[TimeSeriesStartingTime] = Field(None, description="""Timestamp of the first sample in seconds. When timestamps are uniformly spaced, the timestamp of the first sample can be specified and all subsequent ones calculated from the sampling rate attribute.""")
-#     timestamps: Optional[TimeSeriesTimestamps] = Field(None, description="""Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time.""")
-#     control: Optional[TimeSeriesControl] = Field(None, description="""Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data.""")
-#     control_description: Optional[TimeSeriesControlDescription] = Field(None, description="""Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0.""")
-#     sync: Optional[TimeSeriesSync] = Field(None, description="""Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of 'sync' are mostly for archival purposes.""")
-#
-#
-#
-# # Update forward refs
-# # see https://pydantic-docs.helpmanual.io/usage/postponed_annotations/
-# GrayscaleImage.update_forward_refs()
-# RGBImage.update_forward_refs()
-# RGBAImage.update_forward_refs()
-# ImageSeries.update_forward_refs()
-# ImageMaskSeries.update_forward_refs()
-# OpticalSeries.update_forward_refs()
-# IndexSeries.update_forward_refs()
+
+class ImageSeries(TimeSeries):
+    """
+    General image data that is common between acquisition and stimulus time series. Sometimes the image data is stored in the file in a raw format while other times it will be stored as a series of external image files in the host file system. The data field will either be binary data, if the data is stored in the NWB file, or empty, if the data is stored in an external image stack. [frame][x][y] or [frame][x][y][z].
+    """
+    name: str = Field(...)
+    data: ImageSeriesData = Field(..., description="""Binary data representing images across frames. If data are stored in an external file, this should be an empty 3D array.""")
+    dimension: Optional[List[int]] = Field(default_factory=list, description="""Number of pixels on x, y, (and z) axes.""")
+    external_file: Optional[List[str]] = Field(default_factory=list, description="""Paths to one or more external file(s). The field is only present if format='external'. This is only relevant if the image series is stored in the file system as one or more image file(s). This field should NOT be used if the image is stored in another NWB file and that file is linked to this file.""")
+    format: Optional[str] = Field(None, description="""Format of image. If this is 'external', then the attribute 'external_file' contains the path information to the image files. If this is 'raw', then the raw (single-channel) binary data is stored in the 'data' dataset. If this attribute is not present, then the default format='raw' case is assumed.""")
+    description: Optional[str] = Field(None, description="""Description of the time series.""")
+    comments: Optional[str] = Field(None, description="""Human-readable comments about the TimeSeries. This second descriptive field can be used to store additional information, or descriptive information if the primary description field is populated with a computer-readable string.""")
+    starting_time: Optional[TimeSeriesStartingTime] = Field(None, description="""Timestamp of the first sample in seconds. When timestamps are uniformly spaced, the timestamp of the first sample can be specified and all subsequent ones calculated from the sampling rate attribute.""")
+    timestamps: Optional[List[float]] = Field(default_factory=list, description="""Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time.""")
+    control: Optional[List[int]] = Field(default_factory=list, description="""Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data.""")
+    control_description: Optional[List[str]] = Field(default_factory=list, description="""Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0.""")
+    sync: Optional[TimeSeriesSync] = Field(None, description="""Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of 'sync' are mostly for archival purposes.""")
+    
+
+class ImageMaskSeries(ImageSeries):
+    """
+    An alpha mask that is applied to a presented visual stimulus. The 'data' array contains an array of mask values that are applied to the displayed image. Mask values are stored as RGBA. Mask can vary with time. The timestamps array indicates the starting time of a mask, and that mask pattern continues until it's explicitly changed.
+    """
+    name: str = Field(...)
+    data: ImageSeriesData = Field(..., description="""Binary data representing images across frames. If data are stored in an external file, this should be an empty 3D array.""")
+    dimension: Optional[List[int]] = Field(default_factory=list, description="""Number of pixels on x, y, (and z) axes.""")
+    external_file: Optional[List[str]] = Field(default_factory=list, description="""Paths to one or more external file(s). The field is only present if format='external'. This is only relevant if the image series is stored in the file system as one or more image file(s). This field should NOT be used if the image is stored in another NWB file and that file is linked to this file.""")
+    format: Optional[str] = Field(None, description="""Format of image. If this is 'external', then the attribute 'external_file' contains the path information to the image files. If this is 'raw', then the raw (single-channel) binary data is stored in the 'data' dataset. If this attribute is not present, then the default format='raw' case is assumed.""")
+    description: Optional[str] = Field(None, description="""Description of the time series.""")
+    comments: Optional[str] = Field(None, description="""Human-readable comments about the TimeSeries. This second descriptive field can be used to store additional information, or descriptive information if the primary description field is populated with a computer-readable string.""")
+    starting_time: Optional[TimeSeriesStartingTime] = Field(None, description="""Timestamp of the first sample in seconds. When timestamps are uniformly spaced, the timestamp of the first sample can be specified and all subsequent ones calculated from the sampling rate attribute.""")
+    timestamps: Optional[List[float]] = Field(default_factory=list, description="""Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time.""")
+    control: Optional[List[int]] = Field(default_factory=list, description="""Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data.""")
+    control_description: Optional[List[str]] = Field(default_factory=list, description="""Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0.""")
+    sync: Optional[TimeSeriesSync] = Field(None, description="""Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of 'sync' are mostly for archival purposes.""")
+    
+
+class OpticalSeries(ImageSeries):
+    """
+    Image data that is presented or recorded. A stimulus template movie will be stored only as an image. When the image is presented as stimulus, additional data is required, such as field of view (e.g., how much of the visual field the image covers, or how what is the area of the target being imaged). If the OpticalSeries represents acquired imaging data, orientation is also important.
+    """
+    name: str = Field(...)
+    distance: Optional[float] = Field(None, description="""Distance from camera/monitor to target/eye.""")
+    field_of_view: Optional[OpticalSeriesFieldOfView] = Field(None, description="""Width, height and depth of image, or imaged area, in meters.""")
+    data: OpticalSeriesData = Field(..., description="""Images presented to subject, either grayscale or RGB""")
+    orientation: Optional[str] = Field(None, description="""Description of image relative to some reference frame (e.g., which way is up). Must also specify frame of reference.""")
+    dimension: Optional[List[int]] = Field(default_factory=list, description="""Number of pixels on x, y, (and z) axes.""")
+    external_file: Optional[List[str]] = Field(default_factory=list, description="""Paths to one or more external file(s). The field is only present if format='external'. This is only relevant if the image series is stored in the file system as one or more image file(s). This field should NOT be used if the image is stored in another NWB file and that file is linked to this file.""")
+    format: Optional[str] = Field(None, description="""Format of image. If this is 'external', then the attribute 'external_file' contains the path information to the image files. If this is 'raw', then the raw (single-channel) binary data is stored in the 'data' dataset. If this attribute is not present, then the default format='raw' case is assumed.""")
+    description: Optional[str] = Field(None, description="""Description of the time series.""")
+    comments: Optional[str] = Field(None, description="""Human-readable comments about the TimeSeries. This second descriptive field can be used to store additional information, or descriptive information if the primary description field is populated with a computer-readable string.""")
+    starting_time: Optional[TimeSeriesStartingTime] = Field(None, description="""Timestamp of the first sample in seconds. When timestamps are uniformly spaced, the timestamp of the first sample can be specified and all subsequent ones calculated from the sampling rate attribute.""")
+    timestamps: Optional[List[float]] = Field(default_factory=list, description="""Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time.""")
+    control: Optional[List[int]] = Field(default_factory=list, description="""Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data.""")
+    control_description: Optional[List[str]] = Field(default_factory=list, description="""Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0.""")
+    sync: Optional[TimeSeriesSync] = Field(None, description="""Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of 'sync' are mostly for archival purposes.""")
+    
+
+class IndexSeries(TimeSeries):
+    """
+    Stores indices to image frames stored in an ImageSeries. The purpose of the IndexSeries is to allow a static image stack to be stored in an Images object, and the images in the stack to be referenced out-of-order. This can be for the display of individual images, or of movie segments (as a movie is simply a series of images). The data field stores the index of the frame in the referenced Images object, and the timestamps array indicates when that image was displayed.
+    """
+    name: str = Field(...)
+    data: List[int] = Field(default_factory=list, description="""Index of the image (using zero-indexing) in the linked Images object.""")
+    description: Optional[str] = Field(None, description="""Description of the time series.""")
+    comments: Optional[str] = Field(None, description="""Human-readable comments about the TimeSeries. This second descriptive field can be used to store additional information, or descriptive information if the primary description field is populated with a computer-readable string.""")
+    starting_time: Optional[TimeSeriesStartingTime] = Field(None, description="""Timestamp of the first sample in seconds. When timestamps are uniformly spaced, the timestamp of the first sample can be specified and all subsequent ones calculated from the sampling rate attribute.""")
+    timestamps: Optional[List[float]] = Field(default_factory=list, description="""Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time.""")
+    control: Optional[List[int]] = Field(default_factory=list, description="""Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data.""")
+    control_description: Optional[List[str]] = Field(default_factory=list, description="""Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0.""")
+    sync: Optional[TimeSeriesSync] = Field(None, description="""Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of 'sync' are mostly for archival purposes.""")
+    
+
+
+# Model rebuild
+# see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
+GrayscaleImage.model_rebuild()
+RGBImage.model_rebuild()
+RGBAImage.model_rebuild()
+ImageSeries.model_rebuild()
+ImageMaskSeries.model_rebuild()
+OpticalSeries.model_rebuild()
+IndexSeries.model_rebuild()
+    

nwb_linkml/models/core_nwb_image_include.py

@@ -19,13 +19,9 @@ from .nwb_language import (
 metamodel_version = "None"
 version = "None"
 
-class WeakRefShimBaseModel(BaseModel):
-   __slots__ = '__weakref__'
-
-class ConfiguredBaseModel(WeakRefShimBaseModel,
+class ConfiguredBaseModel(BaseModel,
                 validate_assignment = True,
-                validate_all = True,
-                underscore_attrs_are_private = True,
+                validate_default = True,
                 extra = 'forbid',
                 arbitrary_types_allowed = True,
                 use_enum_values = True):
@@ -34,29 +30,33 @@ class ConfiguredBaseModel(WeakRefShimBaseModel,
 
 class GrayscaleImageArray(Arraylike):
     
-    x: Optional[float] = Field(None)
-    y: Optional[float] = Field(None)
+    x: float = Field(...)
+    y: float = Field(...)
     
 
 class RGBImageArray(Arraylike):
     
-    x: Optional[float] = Field(None)
-    y: Optional[float] = Field(None)
-    r_g_b: Optional[float] = Field(None)
+    x: float = Field(...)
+    y: float = Field(...)
+    r_g_b: float = Field(...)
     
 
 class RGBAImageArray(Arraylike):
     
-    x: Optional[float] = Field(None)
-    y: Optional[float] = Field(None)
-    r_g_b_a: Optional[float] = Field(None)
+    x: float = Field(...)
+    y: float = Field(...)
+    r_g_b_a: float = Field(...)
     
 
 class ImageSeriesData(ConfiguredBaseModel):
     """
     Binary data representing images across frames. If data are stored in an external file, this should be an empty 3D array.
     """
-    array: Optional[NDArray[Shape["* frame, * x, * y, * z"], Number]] = Field(None)
+    name: str = Field("data", const=True)
+    array: Optional[Union[
+        NDArray[Shape["* frame, * x, * y"], Number],
+        NDArray[Shape["* frame, * x, * y, * z"], Number]
+    ]] = Field(None)
     
 
 class ImageSeriesDataArray(Arraylike):
@@ -67,26 +67,15 @@ class ImageSeriesDataArray(Arraylike):
     z: Optional[float] = Field(None)
     
 
-class ImageSeriesDimension(ConfiguredBaseModel):
-    """
-    Number of pixels on x, y, (and z) axes.
-    """
-    dimension: Optional[List[int]] = Field(default_factory=list, description="""Number of pixels on x, y, (and z) axes.""")
-    
-
-class ImageSeriesExternalFile(ConfiguredBaseModel):
-    """
-    Paths to one or more external file(s). The field is only present if format='external'. This is only relevant if the image series is stored in the file system as one or more image file(s). This field should NOT be used if the image is stored in another NWB file and that file is linked to this file.
-    """
-    starting_frame: Optional[int] = Field(None, description="""Each external image may contain one or more consecutive frames of the full ImageSeries. This attribute serves as an index to indicate which frames each file contains, to facilitate random access. The 'starting_frame' attribute, hence, contains a list of frame numbers within the full ImageSeries of the first frame of each file listed in the parent 'external_file' dataset. Zero-based indexing is used (hence, the first element will always be zero). For example, if the 'external_file' dataset has three paths to files and the first file has 5 frames, the second file has 10 frames, and the third file has 20 frames, then this attribute will have values [0, 5, 15]. If there is a single external file that holds all of the frames of the ImageSeries (and so there is a single element in the 'external_file' dataset), then this attribute should have value [0].""")
-    external_file: Optional[List[str]] = Field(default_factory=list, description="""Paths to one or more external file(s). The field is only present if format='external'. This is only relevant if the image series is stored in the file system as one or more image file(s). This field should NOT be used if the image is stored in another NWB file and that file is linked to this file.""")
-    
-
 class OpticalSeriesFieldOfView(ConfiguredBaseModel):
     """
     Width, height and depth of image, or imaged area, in meters.
     """
-    array: Optional[NDArray[Shape["2 width_height, 3 width_height_depth"], Float32]] = Field(None)
+    name: str = Field("field_of_view", const=True)
+    array: Optional[Union[
+        NDArray[Shape["2 width_height"], Float32],
+        NDArray[Shape["2 width_height, 3 width_height_depth"], Float32]
+    ]] = Field(None)
     
 
 class OpticalSeriesFieldOfViewArray(Arraylike):
@@ -99,7 +88,11 @@ class OpticalSeriesData(ConfiguredBaseModel):
     """
     Images presented to subject, either grayscale or RGB
     """
-    array: Optional[NDArray[Shape["* frame, * x, * y, 3 r_g_b"], Number]] = Field(None)
+    name: str = Field("data", const=True)
+    array: Optional[Union[
+        NDArray[Shape["* frame, * x, * y"], Number],
+        NDArray[Shape["* frame, * x, * y, 3 r_g_b"], Number]
+    ]] = Field(None)
     
 
 class OpticalSeriesDataArray(Arraylike):
@@ -110,29 +103,16 @@ class OpticalSeriesDataArray(Arraylike):
     r_g_b: Optional[float] = Field(None)
     
 
-class IndexSeriesData(ConfiguredBaseModel):
-    """
-    Index of the image (using zero-indexing) in the linked Images object.
-    """
-    conversion: Optional[float] = Field(None, description="""This field is unused by IndexSeries.""")
-    resolution: Optional[float] = Field(None, description="""This field is unused by IndexSeries.""")
-    offset: Optional[float] = Field(None, description="""This field is unused by IndexSeries.""")
-    unit: Optional[str] = Field(None, description="""This field is unused by IndexSeries and has the value N/A.""")
-    data: List[int] = Field(default_factory=list, description="""Index of the image (using zero-indexing) in the linked Images object.""")
 
+# Model rebuild
+# see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
+GrayscaleImageArray.model_rebuild()
+RGBImageArray.model_rebuild()
+RGBAImageArray.model_rebuild()
+ImageSeriesData.model_rebuild()
+ImageSeriesDataArray.model_rebuild()
+OpticalSeriesFieldOfView.model_rebuild()
+OpticalSeriesFieldOfViewArray.model_rebuild()
+OpticalSeriesData.model_rebuild()
+OpticalSeriesDataArray.model_rebuild()
     
-
-# Update forward refs
-# see https://pydantic-docs.helpmanual.io/usage/postponed_annotations/
-GrayscaleImageArray.update_forward_refs()
-RGBImageArray.update_forward_refs()
-RGBAImageArray.update_forward_refs()
-ImageSeriesData.update_forward_refs()
-ImageSeriesDataArray.update_forward_refs()
-ImageSeriesDimension.update_forward_refs()
-ImageSeriesExternalFile.update_forward_refs()
-OpticalSeriesFieldOfView.update_forward_refs()
-OpticalSeriesFieldOfViewArray.update_forward_refs()
-OpticalSeriesData.update_forward_refs()
-OpticalSeriesDataArray.update_forward_refs()
-IndexSeriesData.update_forward_refs()

nwb_linkml/models/core_nwb_misc.py

@@ -11,26 +11,25 @@ else:
     from typing_extensions import Literal
 
 
+from .hdmf_common_table import (
+    DynamicTable
+)
+
 from .core_nwb_misc_include import (
-    AbstractFeatureSeriesFeatures,
+    UnitsElectrodes,
     UnitsElectrodesIndex,
     UnitsObsIntervalsIndex,
-    DecompositionSeriesData,
     UnitsSpikeTimes,
-    UnitsWaveformMean,
-    UnitsWaveformsIndexIndex,
-    UnitsWaveforms,
-    UnitsWaveformsIndex,
-    AnnotationSeriesData,
-    UnitsObsIntervals,
-    AbstractFeatureSeriesFeatureUnits,
-    DecompositionSeriesBands,
+    UnitsSpikeTimesIndex,
     UnitsWaveformSd,
-    UnitsElectrodes,
-    IntervalSeriesData,
-    DecompositionSeriesSourceChannels,
+    UnitsWaveformMean,
+    UnitsWaveforms,
     AbstractFeatureSeriesData,
-    UnitsSpikeTimesIndex
+    UnitsWaveformsIndexIndex,
+    UnitsObsIntervals,
+    UnitsWaveformsIndex,
+    DecompositionSeriesData,
+    DecompositionSeriesSourceChannels
 )
 
 from .core_nwb_base import (
@@ -41,21 +40,13 @@ from .core_nwb_ecephys import (
     ElectrodeGroup
 )
 
-from .hdmf_common_table import (
-    DynamicTable
-)
-
 
 metamodel_version = "None"
 version = "None"
 
-class WeakRefShimBaseModel(BaseModel):
-   __slots__ = '__weakref__'
-
-class ConfiguredBaseModel(WeakRefShimBaseModel,
+class ConfiguredBaseModel(BaseModel,
                 validate_assignment = True,
-                validate_all = True,
-                underscore_attrs_are_private = True,
+                validate_default = True,
                 extra = 'forbid',
                 arbitrary_types_allowed = True,
                 use_enum_values = True):
@@ -66,15 +57,16 @@ class AbstractFeatureSeries(TimeSeries):
     """
     Abstract features, such as quantitative descriptions of sensory stimuli. The TimeSeries::data field is a 2D array, storing those features (e.g., for visual grating stimulus this might be orientation, spatial frequency and contrast). Null stimuli (eg, uniform gray) can be marked as being an independent feature (eg, 1.0 for gray, 0.0 for actual stimulus) or by storing NaNs for feature values, or through use of the TimeSeries::control fields. A set of features is considered to persist until the next set of features is defined. The final set of features stored should be the null set. This is useful when storing the raw stimulus is impractical.
     """
+    name: str = Field(...)
     data: AbstractFeatureSeriesData = Field(..., description="""Values of each feature at each time.""")
-    feature_units: Optional[AbstractFeatureSeriesFeatureUnits] = Field(None, description="""Units of each feature.""")
-    features: AbstractFeatureSeriesFeatures = Field(..., description="""Description of the features represented in TimeSeries::data.""")
+    feature_units: Optional[List[str]] = Field(default_factory=list, description="""Units of each feature.""")
+    features: List[str] = Field(default_factory=list, description="""Description of the features represented in TimeSeries::data.""")
     description: Optional[str] = Field(None, description="""Description of the time series.""")
     comments: Optional[str] = Field(None, description="""Human-readable comments about the TimeSeries. This second descriptive field can be used to store additional information, or descriptive information if the primary description field is populated with a computer-readable string.""")
     starting_time: Optional[TimeSeriesStartingTime] = Field(None, description="""Timestamp of the first sample in seconds. When timestamps are uniformly spaced, the timestamp of the first sample can be specified and all subsequent ones calculated from the sampling rate attribute.""")
-    timestamps: Optional[TimeSeriesTimestamps] = Field(None, description="""Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time.""")
-    control: Optional[TimeSeriesControl] = Field(None, description="""Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data.""")
-    control_description: Optional[TimeSeriesControlDescription] = Field(None, description="""Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0.""")
+    timestamps: Optional[List[float]] = Field(default_factory=list, description="""Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time.""")
+    control: Optional[List[int]] = Field(default_factory=list, description="""Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data.""")
+    control_description: Optional[List[str]] = Field(default_factory=list, description="""Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0.""")
     sync: Optional[TimeSeriesSync] = Field(None, description="""Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of 'sync' are mostly for archival purposes.""")
     
 
@@ -82,13 +74,14 @@ class AnnotationSeries(TimeSeries):
     """
     Stores user annotations made during an experiment. The data[] field stores a text array, and timestamps are stored for each annotation (ie, interval=1). This is largely an alias to a standard TimeSeries storing a text array but that is identifiable as storing annotations in a machine-readable way.
     """
-    data: AnnotationSeriesData = Field(..., description="""Annotations made during an experiment.""")
+    name: str = Field(...)
+    data: List[str] = Field(default_factory=list, description="""Annotations made during an experiment.""")
     description: Optional[str] = Field(None, description="""Description of the time series.""")
     comments: Optional[str] = Field(None, description="""Human-readable comments about the TimeSeries. This second descriptive field can be used to store additional information, or descriptive information if the primary description field is populated with a computer-readable string.""")
     starting_time: Optional[TimeSeriesStartingTime] = Field(None, description="""Timestamp of the first sample in seconds. When timestamps are uniformly spaced, the timestamp of the first sample can be specified and all subsequent ones calculated from the sampling rate attribute.""")
-    timestamps: Optional[TimeSeriesTimestamps] = Field(None, description="""Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time.""")
-    control: Optional[TimeSeriesControl] = Field(None, description="""Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data.""")
-    control_description: Optional[TimeSeriesControlDescription] = Field(None, description="""Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0.""")
+    timestamps: Optional[List[float]] = Field(default_factory=list, description="""Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time.""")
+    control: Optional[List[int]] = Field(default_factory=list, description="""Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data.""")
+    control_description: Optional[List[str]] = Field(default_factory=list, description="""Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0.""")
     sync: Optional[TimeSeriesSync] = Field(None, description="""Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of 'sync' are mostly for archival purposes.""")
     
 
@@ -96,13 +89,14 @@ class IntervalSeries(TimeSeries):
     """
     Stores intervals of data. The timestamps field stores the beginning and end of intervals. The data field stores whether the interval just started (>0 value) or ended (<0 value). Different interval types can be represented in the same series by using multiple key values (eg, 1 for feature A, 2 for feature B, 3 for feature C, etc). The field data stores an 8-bit integer. This is largely an alias of a standard TimeSeries but that is identifiable as representing time intervals in a machine-readable way.
     """
-    data: IntervalSeriesData = Field(..., description="""Use values >0 if interval started, <0 if interval ended.""")
+    name: str = Field(...)
+    data: List[int] = Field(default_factory=list, description="""Use values >0 if interval started, <0 if interval ended.""")
     description: Optional[str] = Field(None, description="""Description of the time series.""")
     comments: Optional[str] = Field(None, description="""Human-readable comments about the TimeSeries. This second descriptive field can be used to store additional information, or descriptive information if the primary description field is populated with a computer-readable string.""")
     starting_time: Optional[TimeSeriesStartingTime] = Field(None, description="""Timestamp of the first sample in seconds. When timestamps are uniformly spaced, the timestamp of the first sample can be specified and all subsequent ones calculated from the sampling rate attribute.""")
-    timestamps: Optional[TimeSeriesTimestamps] = Field(None, description="""Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time.""")
-    control: Optional[TimeSeriesControl] = Field(None, description="""Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data.""")
-    control_description: Optional[TimeSeriesControlDescription] = Field(None, description="""Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0.""")
+    timestamps: Optional[List[float]] = Field(default_factory=list, description="""Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time.""")
+    control: Optional[List[int]] = Field(default_factory=list, description="""Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data.""")
+    control_description: Optional[List[str]] = Field(default_factory=list, description="""Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0.""")
     sync: Optional[TimeSeriesSync] = Field(None, description="""Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of 'sync' are mostly for archival purposes.""")
     
 
@@ -110,16 +104,17 @@ class DecompositionSeries(TimeSeries):
     """
     Spectral analysis of a time series, e.g. of an LFP or a speech signal.
     """
+    name: str = Field(...)
     data: DecompositionSeriesData = Field(..., description="""Data decomposed into frequency bands.""")
     metric: str = Field(..., description="""The metric used, e.g. phase, amplitude, power.""")
     source_channels: Optional[DecompositionSeriesSourceChannels] = Field(None, description="""DynamicTableRegion pointer to the channels that this decomposition series was generated from.""")
-    bands: DecompositionSeriesBands = Field(..., description="""Table for describing the bands that this series was generated from. There should be one row in this table for each band.""")
+    bands: DynamicTable = Field(..., description="""Table for describing the bands that this series was generated from. There should be one row in this table for each band.""")
     description: Optional[str] = Field(None, description="""Description of the time series.""")
     comments: Optional[str] = Field(None, description="""Human-readable comments about the TimeSeries. This second descriptive field can be used to store additional information, or descriptive information if the primary description field is populated with a computer-readable string.""")
     starting_time: Optional[TimeSeriesStartingTime] = Field(None, description="""Timestamp of the first sample in seconds. When timestamps are uniformly spaced, the timestamp of the first sample can be specified and all subsequent ones calculated from the sampling rate attribute.""")
-    timestamps: Optional[TimeSeriesTimestamps] = Field(None, description="""Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time.""")
-    control: Optional[TimeSeriesControl] = Field(None, description="""Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data.""")
-    control_description: Optional[TimeSeriesControlDescription] = Field(None, description="""Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0.""")
+    timestamps: Optional[List[float]] = Field(default_factory=list, description="""Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time.""")
+    control: Optional[List[int]] = Field(default_factory=list, description="""Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data.""")
+    control_description: Optional[List[str]] = Field(default_factory=list, description="""Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0.""")
     sync: Optional[TimeSeriesSync] = Field(None, description="""Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of 'sync' are mostly for archival purposes.""")
     
 
@@ -127,6 +122,7 @@ class Units(DynamicTable):
     """
     Data about spiking units. Event times of observed units (e.g. cell, synapse, etc.) should be concatenated and stored in spike_times.
     """
+    name: str = Field(...)
     spike_times_index: Optional[UnitsSpikeTimesIndex] = Field(None, description="""Index into the spike_times dataset.""")
     spike_times: Optional[UnitsSpikeTimes] = Field(None, description="""Spike times for each unit in seconds.""")
     obs_intervals_index: Optional[UnitsObsIntervalsIndex] = Field(None, description="""Index into the obs_intervals dataset.""")
@@ -141,15 +137,16 @@ class Units(DynamicTable):
     waveforms_index_index: Optional[UnitsWaveformsIndexIndex] = Field(None, description="""Index into the waveforms_index dataset. One value for every unit (row in the table). See 'waveforms' for more detail.""")
     colnames: Optional[str] = Field(None, description="""The names of the columns in this table. This should be used to specify an order to the columns.""")
     description: Optional[str] = Field(None, description="""Description of what is in this dynamic table.""")
-    id: DynamicTableId = Field(..., description="""Array of unique identifiers for the rows of this dynamic table.""")
+    id: List[int] = Field(default_factory=list, description="""Array of unique identifiers for the rows of this dynamic table.""")
     VectorData: Optional[List[VectorData]] = Field(default_factory=list, description="""Vector columns, including index columns, of this dynamic table.""")
     
 
 
-# Update forward refs
-# see https://pydantic-docs.helpmanual.io/usage/postponed_annotations/
-AbstractFeatureSeries.update_forward_refs()
-AnnotationSeries.update_forward_refs()
-IntervalSeries.update_forward_refs()
-DecompositionSeries.update_forward_refs()
-Units.update_forward_refs()
+# Model rebuild
+# see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
+AbstractFeatureSeries.model_rebuild()
+AnnotationSeries.model_rebuild()
+IntervalSeries.model_rebuild()
+DecompositionSeries.model_rebuild()
+Units.model_rebuild()
+    

nwb_linkml/models/core_nwb_misc_include.py

@@ -13,9 +13,8 @@ else:
 
 from .hdmf_common_table import (
     DynamicTableRegion,
-    DynamicTable,
-    VectorIndex,
-    VectorData
+    VectorData,
+    VectorIndex
 )
 
 from .nwb_language import (
@@ -26,13 +25,9 @@ from .nwb_language import (
 metamodel_version = "None"
 version = "None"
 
-class WeakRefShimBaseModel(BaseModel):
-   __slots__ = '__weakref__'
-
-class ConfiguredBaseModel(WeakRefShimBaseModel,
+class ConfiguredBaseModel(BaseModel,
                 validate_assignment = True,
-                validate_all = True,
-                underscore_attrs_are_private = True,
+                validate_default = True,
                 extra = 'forbid',
                 arbitrary_types_allowed = True,
                 use_enum_values = True):
@@ -43,8 +38,12 @@ class AbstractFeatureSeriesData(ConfiguredBaseModel):
     """
     Values of each feature at each time.
     """
+    name: str = Field("data", const=True)
     unit: Optional[str] = Field(None, description="""Since there can be different units for different features, store the units in 'feature_units'. The default value for this attribute is \"see 'feature_units'\".""")
-    array: Optional[NDArray[Shape["* num_times, * num_features"], Number]] = Field(None)
+    array: Optional[Union[
+        NDArray[Shape["* num_times"], Number],
+        NDArray[Shape["* num_times, * num_features"], Number]
+    ]] = Field(None)
     
 
 class AbstractFeatureSeriesDataArray(Arraylike):
@@ -53,225 +52,221 @@ class AbstractFeatureSeriesDataArray(Arraylike):
     num_features: Optional[float] = Field(None)
     
 
-class AbstractFeatureSeriesFeatureUnits(ConfiguredBaseModel):
-    """
-    Units of each feature.
-    """
-    feature_units: Optional[List[str]] = Field(default_factory=list, description="""Units of each feature.""")
-    
-
-class AbstractFeatureSeriesFeatures(ConfiguredBaseModel):
-    """
-    Description of the features represented in TimeSeries::data.
-    """
-    features: List[str] = Field(default_factory=list, description="""Description of the features represented in TimeSeries::data.""")
-    
-
-class AnnotationSeriesData(ConfiguredBaseModel):
-    """
-    Annotations made during an experiment.
-    """
-    resolution: Optional[float] = Field(None, description="""Smallest meaningful difference between values in data. Annotations have no units, so the value is fixed to -1.0.""")
-    unit: Optional[str] = Field(None, description="""Base unit of measurement for working with the data. Annotations have no units, so the value is fixed to 'n/a'.""")
-    data: List[str] = Field(default_factory=list, description="""Annotations made during an experiment.""")
-    
-
-class IntervalSeriesData(ConfiguredBaseModel):
-    """
-    Use values >0 if interval started, <0 if interval ended.
-    """
-    resolution: Optional[float] = Field(None, description="""Smallest meaningful difference between values in data. Annotations have no units, so the value is fixed to -1.0.""")
-    unit: Optional[str] = Field(None, description="""Base unit of measurement for working with the data. Annotations have no units, so the value is fixed to 'n/a'.""")
-    data: List[int] = Field(default_factory=list, description="""Use values >0 if interval started, <0 if interval ended.""")
-    
-
 class DecompositionSeriesData(ConfiguredBaseModel):
     """
     Data decomposed into frequency bands.
     """
+    name: str = Field("data", const=True)
     unit: Optional[str] = Field(None, description="""Base unit of measurement for working with the data. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""")
     array: Optional[NDArray[Shape["* num_times, * num_channels, * num_bands"], Number]] = Field(None)
     
 
 class DecompositionSeriesDataArray(Arraylike):
     
-    num_times: Optional[float] = Field(None)
-    num_channels: Optional[float] = Field(None)
-    num_bands: Optional[float] = Field(None)
+    num_times: float = Field(...)
+    num_channels: float = Field(...)
+    num_bands: float = Field(...)
     
 
 class DecompositionSeriesSourceChannels(DynamicTableRegion):
     """
     DynamicTableRegion pointer to the channels that this decomposition series was generated from.
     """
+    name: str = Field("source_channels", const=True)
     table: Optional[DynamicTable] = Field(None, description="""Reference to the DynamicTable object that this region applies to.""")
     description: Optional[str] = Field(None, description="""Description of what this table region points to.""")
-    array: Optional[NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], ]] = Field(None)
-    
-
-class DecompositionSeriesBands(DynamicTable):
-    """
-    Table for describing the bands that this series was generated from. There should be one row in this table for each band.
-    """
-    band_name: Optional[List[str]] = Field(default_factory=list, description="""Name of the band, e.g. theta.""")
-    band_limits: DecompositionSeriesBandsBandLimits = Field(..., description="""Low and high limit of each band in Hz. If it is a Gaussian filter, use 2 SD on either side of the center.""")
-    band_mean: DecompositionSeriesBandsBandMean = Field(..., description="""The mean Gaussian filters, in Hz.""")
-    band_stdev: DecompositionSeriesBandsBandStdev = Field(..., description="""The standard deviation of Gaussian filters, in Hz.""")
-    colnames: Optional[str] = Field(None, description="""The names of the columns in this table. This should be used to specify an order to the columns.""")
-    description: Optional[str] = Field(None, description="""Description of what is in this dynamic table.""")
-    id: DynamicTableId = Field(..., description="""Array of unique identifiers for the rows of this dynamic table.""")
-    VectorData: Optional[List[VectorData]] = Field(default_factory=list, description="""Vector columns, including index columns, of this dynamic table.""")
-    
-
-class DecompositionSeriesBandsBandLimits(VectorData):
-    """
-    Low and high limit of each band in Hz. If it is a Gaussian filter, use 2 SD on either side of the center.
-    """
-    description: Optional[str] = Field(None, description="""Description of what these vectors represent.""")
-    array: Optional[NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], ]] = Field(None)
-    
-
-class DecompositionSeriesBandsBandMean(VectorData):
-    """
-    The mean Gaussian filters, in Hz.
-    """
-    description: Optional[str] = Field(None, description="""Description of what these vectors represent.""")
-    array: Optional[NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], ]] = Field(None)
-    
-
-class DecompositionSeriesBandsBandStdev(VectorData):
-    """
-    The standard deviation of Gaussian filters, in Hz.
-    """
-    description: Optional[str] = Field(None, description="""Description of what these vectors represent.""")
-    array: Optional[NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], ]] = Field(None)
+    array: Optional[Union[
+        NDArray[Shape["* dim0"], Any],
+        NDArray[Shape["* dim0, * dim1"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], Any]
+    ]] = Field(None)
     
 
 class UnitsSpikeTimesIndex(VectorIndex):
     """
     Index into the spike_times dataset.
     """
+    name: str = Field("spike_times_index", const=True)
     target: Optional[VectorData] = Field(None, description="""Reference to the target dataset that this index applies to.""")
     description: Optional[str] = Field(None, description="""Description of what these vectors represent.""")
-    array: Optional[NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], ]] = Field(None)
+    array: Optional[Union[
+        NDArray[Shape["* dim0"], Any],
+        NDArray[Shape["* dim0, * dim1"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], Any]
+    ]] = Field(None)
     
 
 class UnitsSpikeTimes(VectorData):
     """
     Spike times for each unit in seconds.
     """
+    name: str = Field("spike_times", const=True)
     resolution: Optional[float] = Field(None, description="""The smallest possible difference between two spike times. Usually 1 divided by the acquisition sampling rate from which spike times were extracted, but could be larger if the acquisition time series was downsampled or smaller if the acquisition time series was smoothed/interpolated and it is possible for the spike time to be between samples.""")
     description: Optional[str] = Field(None, description="""Description of what these vectors represent.""")
-    array: Optional[NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], ]] = Field(None)
+    array: Optional[Union[
+        NDArray[Shape["* dim0"], Any],
+        NDArray[Shape["* dim0, * dim1"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], Any]
+    ]] = Field(None)
     
 
 class UnitsObsIntervalsIndex(VectorIndex):
     """
     Index into the obs_intervals dataset.
     """
+    name: str = Field("obs_intervals_index", const=True)
     target: Optional[VectorData] = Field(None, description="""Reference to the target dataset that this index applies to.""")
     description: Optional[str] = Field(None, description="""Description of what these vectors represent.""")
-    array: Optional[NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], ]] = Field(None)
+    array: Optional[Union[
+        NDArray[Shape["* dim0"], Any],
+        NDArray[Shape["* dim0, * dim1"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], Any]
+    ]] = Field(None)
     
 
 class UnitsObsIntervals(VectorData):
     """
     Observation intervals for each unit.
     """
+    name: str = Field("obs_intervals", const=True)
     description: Optional[str] = Field(None, description="""Description of what these vectors represent.""")
-    array: Optional[NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], ]] = Field(None)
+    array: Optional[Union[
+        NDArray[Shape["* dim0"], Any],
+        NDArray[Shape["* dim0, * dim1"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], Any]
+    ]] = Field(None)
     
 
 class UnitsElectrodesIndex(VectorIndex):
     """
     Index into electrodes.
     """
+    name: str = Field("electrodes_index", const=True)
     target: Optional[VectorData] = Field(None, description="""Reference to the target dataset that this index applies to.""")
     description: Optional[str] = Field(None, description="""Description of what these vectors represent.""")
-    array: Optional[NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], ]] = Field(None)
+    array: Optional[Union[
+        NDArray[Shape["* dim0"], Any],
+        NDArray[Shape["* dim0, * dim1"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], Any]
+    ]] = Field(None)
     
 
 class UnitsElectrodes(DynamicTableRegion):
     """
     Electrode that each spike unit came from, specified using a DynamicTableRegion.
     """
+    name: str = Field("electrodes", const=True)
     table: Optional[DynamicTable] = Field(None, description="""Reference to the DynamicTable object that this region applies to.""")
     description: Optional[str] = Field(None, description="""Description of what this table region points to.""")
-    array: Optional[NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], ]] = Field(None)
+    array: Optional[Union[
+        NDArray[Shape["* dim0"], Any],
+        NDArray[Shape["* dim0, * dim1"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], Any]
+    ]] = Field(None)
     
 
 class UnitsWaveformMean(VectorData):
     """
     Spike waveform mean for each spike unit.
     """
+    name: str = Field("waveform_mean", const=True)
     sampling_rate: Optional[float] = Field(None, description="""Sampling rate, in hertz.""")
     unit: Optional[str] = Field(None, description="""Unit of measurement. This value is fixed to 'volts'.""")
     description: Optional[str] = Field(None, description="""Description of what these vectors represent.""")
-    array: Optional[NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], ]] = Field(None)
+    array: Optional[Union[
+        NDArray[Shape["* dim0"], Any],
+        NDArray[Shape["* dim0, * dim1"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], Any]
+    ]] = Field(None)
     
 
 class UnitsWaveformSd(VectorData):
     """
     Spike waveform standard deviation for each spike unit.
     """
+    name: str = Field("waveform_sd", const=True)
     sampling_rate: Optional[float] = Field(None, description="""Sampling rate, in hertz.""")
     unit: Optional[str] = Field(None, description="""Unit of measurement. This value is fixed to 'volts'.""")
     description: Optional[str] = Field(None, description="""Description of what these vectors represent.""")
-    array: Optional[NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], ]] = Field(None)
+    array: Optional[Union[
+        NDArray[Shape["* dim0"], Any],
+        NDArray[Shape["* dim0, * dim1"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], Any]
+    ]] = Field(None)
     
 
 class UnitsWaveforms(VectorData):
     """
     Individual waveforms for each spike on each electrode. This is a doubly indexed column. The 'waveforms_index' column indexes which waveforms in this column belong to the same spike event for a given unit, where each waveform was recorded from a different electrode. The 'waveforms_index_index' column indexes the 'waveforms_index' column to indicate which spike events belong to a given unit. For example, if the 'waveforms_index_index' column has values [2, 5, 6], then the first 2 elements of the 'waveforms_index' column correspond to the 2 spike events of the first unit, the next 3 elements of the 'waveforms_index' column correspond to the 3 spike events of the second unit, and the next 1 element of the 'waveforms_index' column corresponds to the 1 spike event of the third unit. If the 'waveforms_index' column has values [3, 6, 8, 10, 12, 13], then the first 3 elements of the 'waveforms' column contain the 3 spike waveforms that were recorded from 3 different electrodes for the first spike time of the first unit. See https://nwb-schema.readthedocs.io/en/stable/format_description.html#doubly-ragged-arrays for a graphical representation of this example. When there is only one electrode for each unit (i.e., each spike time is associated with a single waveform), then the 'waveforms_index' column will have values 1, 2, ..., N, where N is the number of spike events. The number of electrodes for each spike event should be the same within a given unit. The 'electrodes' column should be used to indicate which electrodes are associated with each unit, and the order of the waveforms within a given unit x spike event should be in the same order as the electrodes referenced in the 'electrodes' column of this table. The number of samples for each waveform must be the same.
     """
+    name: str = Field("waveforms", const=True)
     sampling_rate: Optional[float] = Field(None, description="""Sampling rate, in hertz.""")
     unit: Optional[str] = Field(None, description="""Unit of measurement. This value is fixed to 'volts'.""")
     description: Optional[str] = Field(None, description="""Description of what these vectors represent.""")
-    array: Optional[NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], ]] = Field(None)
+    array: Optional[Union[
+        NDArray[Shape["* dim0"], Any],
+        NDArray[Shape["* dim0, * dim1"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], Any]
+    ]] = Field(None)
     
 
 class UnitsWaveformsIndex(VectorIndex):
     """
     Index into the waveforms dataset. One value for every spike event. See 'waveforms' for more detail.
     """
+    name: str = Field("waveforms_index", const=True)
     target: Optional[VectorData] = Field(None, description="""Reference to the target dataset that this index applies to.""")
     description: Optional[str] = Field(None, description="""Description of what these vectors represent.""")
-    array: Optional[NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], ]] = Field(None)
+    array: Optional[Union[
+        NDArray[Shape["* dim0"], Any],
+        NDArray[Shape["* dim0, * dim1"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], Any]
+    ]] = Field(None)
     
 
 class UnitsWaveformsIndexIndex(VectorIndex):
     """
     Index into the waveforms_index dataset. One value for every unit (row in the table). See 'waveforms' for more detail.
     """
+    name: str = Field("waveforms_index_index", const=True)
     target: Optional[VectorData] = Field(None, description="""Reference to the target dataset that this index applies to.""")
     description: Optional[str] = Field(None, description="""Description of what these vectors represent.""")
-    array: Optional[NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], ]] = Field(None)
+    array: Optional[Union[
+        NDArray[Shape["* dim0"], Any],
+        NDArray[Shape["* dim0, * dim1"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], Any]
+    ]] = Field(None)
     
 
 
-# Update forward refs
-# see https://pydantic-docs.helpmanual.io/usage/postponed_annotations/
-AbstractFeatureSeriesData.update_forward_refs()
-AbstractFeatureSeriesDataArray.update_forward_refs()
-AbstractFeatureSeriesFeatureUnits.update_forward_refs()
-AbstractFeatureSeriesFeatures.update_forward_refs()
-AnnotationSeriesData.update_forward_refs()
-IntervalSeriesData.update_forward_refs()
-DecompositionSeriesData.update_forward_refs()
-DecompositionSeriesDataArray.update_forward_refs()
-DecompositionSeriesSourceChannels.update_forward_refs()
-DecompositionSeriesBands.update_forward_refs()
-DecompositionSeriesBandsBandLimits.update_forward_refs()
-DecompositionSeriesBandsBandMean.update_forward_refs()
-DecompositionSeriesBandsBandStdev.update_forward_refs()
-UnitsSpikeTimesIndex.update_forward_refs()
-UnitsSpikeTimes.update_forward_refs()
-UnitsObsIntervalsIndex.update_forward_refs()
-UnitsObsIntervals.update_forward_refs()
-UnitsElectrodesIndex.update_forward_refs()
-UnitsElectrodes.update_forward_refs()
-UnitsWaveformMean.update_forward_refs()
-UnitsWaveformSd.update_forward_refs()
-UnitsWaveforms.update_forward_refs()
-UnitsWaveformsIndex.update_forward_refs()
-UnitsWaveformsIndexIndex.update_forward_refs()
+# Model rebuild
+# see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
+AbstractFeatureSeriesData.model_rebuild()
+AbstractFeatureSeriesDataArray.model_rebuild()
+DecompositionSeriesData.model_rebuild()
+DecompositionSeriesDataArray.model_rebuild()
+DecompositionSeriesSourceChannels.model_rebuild()
+UnitsSpikeTimesIndex.model_rebuild()
+UnitsSpikeTimes.model_rebuild()
+UnitsObsIntervalsIndex.model_rebuild()
+UnitsObsIntervals.model_rebuild()
+UnitsElectrodesIndex.model_rebuild()
+UnitsElectrodes.model_rebuild()
+UnitsWaveformMean.model_rebuild()
+UnitsWaveformSd.model_rebuild()
+UnitsWaveforms.model_rebuild()
+UnitsWaveformsIndex.model_rebuild()
+UnitsWaveformsIndexIndex.model_rebuild()
+    

nwb_linkml/models/core_nwb_ogen.py

@@ -16,21 +16,13 @@ from .core_nwb_base import (
     TimeSeries
 )
 
-from .core_nwb_ogen_include import (
-    OptogeneticSeriesData
-)
-
 
 metamodel_version = "None"
 version = "None"
 
-class WeakRefShimBaseModel(BaseModel):
-   __slots__ = '__weakref__'
-
-class ConfiguredBaseModel(WeakRefShimBaseModel,
+class ConfiguredBaseModel(BaseModel,
                 validate_assignment = True,
-                validate_all = True,
-                underscore_attrs_are_private = True,
+                validate_default = True,
                 extra = 'forbid',
                 arbitrary_types_allowed = True,
                 use_enum_values = True):
@@ -41,13 +33,14 @@ class OptogeneticSeries(TimeSeries):
     """
     An optogenetic stimulus.
     """
-    data: OptogeneticSeriesData = Field(..., description="""Applied power for optogenetic stimulus, in watts.""")
+    name: str = Field(...)
+    data: List[float] = Field(default_factory=list, description="""Applied power for optogenetic stimulus, in watts.""")
     description: Optional[str] = Field(None, description="""Description of the time series.""")
     comments: Optional[str] = Field(None, description="""Human-readable comments about the TimeSeries. This second descriptive field can be used to store additional information, or descriptive information if the primary description field is populated with a computer-readable string.""")
     starting_time: Optional[TimeSeriesStartingTime] = Field(None, description="""Timestamp of the first sample in seconds. When timestamps are uniformly spaced, the timestamp of the first sample can be specified and all subsequent ones calculated from the sampling rate attribute.""")
-    timestamps: Optional[TimeSeriesTimestamps] = Field(None, description="""Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time.""")
-    control: Optional[TimeSeriesControl] = Field(None, description="""Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data.""")
-    control_description: Optional[TimeSeriesControlDescription] = Field(None, description="""Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0.""")
+    timestamps: Optional[List[float]] = Field(default_factory=list, description="""Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time.""")
+    control: Optional[List[int]] = Field(default_factory=list, description="""Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data.""")
+    control_description: Optional[List[str]] = Field(default_factory=list, description="""Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0.""")
     sync: Optional[TimeSeriesSync] = Field(None, description="""Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of 'sync' are mostly for archival purposes.""")
     
 
@@ -55,13 +48,15 @@ class OptogeneticStimulusSite(NWBContainer):
     """
     A site of optogenetic stimulation.
     """
+    name: str = Field(...)
     description: str = Field(..., description="""Description of stimulation site.""")
     excitation_lambda: float = Field(..., description="""Excitation wavelength, in nm.""")
     location: str = Field(..., description="""Location of the stimulation site. Specify the area, layer, comments on estimation of area/layer, stereotaxic coordinates if in vivo, etc. Use standard atlas names for anatomical regions when possible.""")
     
 
 
-# Update forward refs
-# see https://pydantic-docs.helpmanual.io/usage/postponed_annotations/
-OptogeneticSeries.update_forward_refs()
-OptogeneticStimulusSite.update_forward_refs()
+# Model rebuild
+# see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
+OptogeneticSeries.model_rebuild()
+OptogeneticStimulusSite.model_rebuild()
+    

nwb_linkml/models/core_nwb_ogen_include.py

@@ -15,13 +15,9 @@ else:
 metamodel_version = "None"
 version = "None"
 
-class WeakRefShimBaseModel(BaseModel):
-   __slots__ = '__weakref__'
-
-class ConfiguredBaseModel(WeakRefShimBaseModel,
+class ConfiguredBaseModel(BaseModel,
                 validate_assignment = True,
-                validate_all = True,
-                underscore_attrs_are_private = True,
+                validate_default = True,
                 extra = 'forbid',
                 arbitrary_types_allowed = True,
                 use_enum_values = True):
@@ -37,6 +33,7 @@ class OptogeneticSeriesData(ConfiguredBaseModel):
     
 
 
-# Update forward refs
-# see https://pydantic-docs.helpmanual.io/usage/postponed_annotations/
-OptogeneticSeriesData.update_forward_refs()
+# Model rebuild
+# see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
+OptogeneticSeriesData.model_rebuild()
+    

nwb_linkml/models/core_nwb_ophys.py

@@ -11,25 +11,22 @@ else:
     from typing_extensions import Literal
 
 
-from .core_nwb_ophys_include import (
-    CorrectedImageStackXyTranslation,
-    PlaneSegmentationVoxelMaskIndex,
-    ImagingPlaneOriginCoords,
-    TwoPhotonSeriesFieldOfView,
-    RoiResponseSeriesRois,
-    CorrectedImageStackCorrected,
-    ImagingPlaneManifold,
-    PlaneSegmentationImageMask,
-    PlaneSegmentationReferenceImages,
-    ImagingPlaneGridSpacing,
-    RoiResponseSeriesData,
-    PlaneSegmentationPixelMaskIndex
-)
-
 from .core_nwb_base import (
     TimeSeries,
-    NWBContainer,
-    NWBDataInterface
+    NWBDataInterface,
+    NWBContainer
+)
+
+from .core_nwb_ophys_include import (
+    RoiResponseSeriesRois,
+    TwoPhotonSeriesFieldOfView,
+    ImagingPlaneOriginCoords,
+    RoiResponseSeriesData,
+    PlaneSegmentationPixelMaskIndex,
+    PlaneSegmentationImageMask,
+    ImagingPlaneGridSpacing,
+    PlaneSegmentationVoxelMaskIndex,
+    ImagingPlaneManifold
 )
 
 from .hdmf_common_table import (
@@ -44,13 +41,9 @@ from .core_nwb_image import (
 metamodel_version = "None"
 version = "None"
 
-class WeakRefShimBaseModel(BaseModel):
-   __slots__ = '__weakref__'
-
-class ConfiguredBaseModel(WeakRefShimBaseModel,
+class ConfiguredBaseModel(BaseModel,
                 validate_assignment = True,
-                validate_all = True,
-                underscore_attrs_are_private = True,
+                validate_default = True,
                 extra = 'forbid',
                 arbitrary_types_allowed = True,
                 use_enum_values = True):
@@ -61,6 +54,7 @@ class OnePhotonSeries(ImageSeries):
     """
     Image stack recorded over time from 1-photon microscope.
     """
+    name: str = Field(...)
     pmt_gain: Optional[float] = Field(None, description="""Photomultiplier gain.""")
     scan_line_rate: Optional[float] = Field(None, description="""Lines imaged per second. This is also stored in /general/optophysiology but is kept here as it is useful information for analysis, and so good to be stored w/ the actual data.""")
     exposure_time: Optional[float] = Field(None, description="""Exposure time of the sample; often the inverse of the frequency.""")
@@ -68,15 +62,15 @@ class OnePhotonSeries(ImageSeries):
     power: Optional[float] = Field(None, description="""Power of the excitation in mW, if known.""")
     intensity: Optional[float] = Field(None, description="""Intensity of the excitation in mW/mm^2, if known.""")
     data: ImageSeriesData = Field(..., description="""Binary data representing images across frames. If data are stored in an external file, this should be an empty 3D array.""")
-    dimension: Optional[ImageSeriesDimension] = Field(None, description="""Number of pixels on x, y, (and z) axes.""")
-    external_file: Optional[ImageSeriesExternalFile] = Field(None, description="""Paths to one or more external file(s). The field is only present if format='external'. This is only relevant if the image series is stored in the file system as one or more image file(s). This field should NOT be used if the image is stored in another NWB file and that file is linked to this file.""")
+    dimension: Optional[List[int]] = Field(default_factory=list, description="""Number of pixels on x, y, (and z) axes.""")
+    external_file: Optional[List[str]] = Field(default_factory=list, description="""Paths to one or more external file(s). The field is only present if format='external'. This is only relevant if the image series is stored in the file system as one or more image file(s). This field should NOT be used if the image is stored in another NWB file and that file is linked to this file.""")
     format: Optional[str] = Field(None, description="""Format of image. If this is 'external', then the attribute 'external_file' contains the path information to the image files. If this is 'raw', then the raw (single-channel) binary data is stored in the 'data' dataset. If this attribute is not present, then the default format='raw' case is assumed.""")
     description: Optional[str] = Field(None, description="""Description of the time series.""")
     comments: Optional[str] = Field(None, description="""Human-readable comments about the TimeSeries. This second descriptive field can be used to store additional information, or descriptive information if the primary description field is populated with a computer-readable string.""")
     starting_time: Optional[TimeSeriesStartingTime] = Field(None, description="""Timestamp of the first sample in seconds. When timestamps are uniformly spaced, the timestamp of the first sample can be specified and all subsequent ones calculated from the sampling rate attribute.""")
-    timestamps: Optional[TimeSeriesTimestamps] = Field(None, description="""Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time.""")
-    control: Optional[TimeSeriesControl] = Field(None, description="""Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data.""")
-    control_description: Optional[TimeSeriesControlDescription] = Field(None, description="""Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0.""")
+    timestamps: Optional[List[float]] = Field(default_factory=list, description="""Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time.""")
+    control: Optional[List[int]] = Field(default_factory=list, description="""Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data.""")
+    control_description: Optional[List[str]] = Field(default_factory=list, description="""Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0.""")
     sync: Optional[TimeSeriesSync] = Field(None, description="""Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of 'sync' are mostly for archival purposes.""")
     
 
@@ -84,19 +78,20 @@ class TwoPhotonSeries(ImageSeries):
     """
     Image stack recorded over time from 2-photon microscope.
     """
+    name: str = Field(...)
     pmt_gain: Optional[float] = Field(None, description="""Photomultiplier gain.""")
     scan_line_rate: Optional[float] = Field(None, description="""Lines imaged per second. This is also stored in /general/optophysiology but is kept here as it is useful information for analysis, and so good to be stored w/ the actual data.""")
     field_of_view: Optional[TwoPhotonSeriesFieldOfView] = Field(None, description="""Width, height and depth of image, or imaged area, in meters.""")
     data: ImageSeriesData = Field(..., description="""Binary data representing images across frames. If data are stored in an external file, this should be an empty 3D array.""")
-    dimension: Optional[ImageSeriesDimension] = Field(None, description="""Number of pixels on x, y, (and z) axes.""")
-    external_file: Optional[ImageSeriesExternalFile] = Field(None, description="""Paths to one or more external file(s). The field is only present if format='external'. This is only relevant if the image series is stored in the file system as one or more image file(s). This field should NOT be used if the image is stored in another NWB file and that file is linked to this file.""")
+    dimension: Optional[List[int]] = Field(default_factory=list, description="""Number of pixels on x, y, (and z) axes.""")
+    external_file: Optional[List[str]] = Field(default_factory=list, description="""Paths to one or more external file(s). The field is only present if format='external'. This is only relevant if the image series is stored in the file system as one or more image file(s). This field should NOT be used if the image is stored in another NWB file and that file is linked to this file.""")
     format: Optional[str] = Field(None, description="""Format of image. If this is 'external', then the attribute 'external_file' contains the path information to the image files. If this is 'raw', then the raw (single-channel) binary data is stored in the 'data' dataset. If this attribute is not present, then the default format='raw' case is assumed.""")
     description: Optional[str] = Field(None, description="""Description of the time series.""")
     comments: Optional[str] = Field(None, description="""Human-readable comments about the TimeSeries. This second descriptive field can be used to store additional information, or descriptive information if the primary description field is populated with a computer-readable string.""")
     starting_time: Optional[TimeSeriesStartingTime] = Field(None, description="""Timestamp of the first sample in seconds. When timestamps are uniformly spaced, the timestamp of the first sample can be specified and all subsequent ones calculated from the sampling rate attribute.""")
-    timestamps: Optional[TimeSeriesTimestamps] = Field(None, description="""Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time.""")
-    control: Optional[TimeSeriesControl] = Field(None, description="""Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data.""")
-    control_description: Optional[TimeSeriesControlDescription] = Field(None, description="""Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0.""")
+    timestamps: Optional[List[float]] = Field(default_factory=list, description="""Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time.""")
+    control: Optional[List[int]] = Field(default_factory=list, description="""Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data.""")
+    control_description: Optional[List[str]] = Field(default_factory=list, description="""Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0.""")
     sync: Optional[TimeSeriesSync] = Field(None, description="""Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of 'sync' are mostly for archival purposes.""")
     
 
@@ -104,14 +99,15 @@ class RoiResponseSeries(TimeSeries):
     """
     ROI responses over an imaging plane. The first dimension represents time. The second dimension, if present, represents ROIs.
     """
+    name: str = Field(...)
     data: RoiResponseSeriesData = Field(..., description="""Signals from ROIs.""")
     rois: RoiResponseSeriesRois = Field(..., description="""DynamicTableRegion referencing into an ROITable containing information on the ROIs stored in this timeseries.""")
     description: Optional[str] = Field(None, description="""Description of the time series.""")
     comments: Optional[str] = Field(None, description="""Human-readable comments about the TimeSeries. This second descriptive field can be used to store additional information, or descriptive information if the primary description field is populated with a computer-readable string.""")
     starting_time: Optional[TimeSeriesStartingTime] = Field(None, description="""Timestamp of the first sample in seconds. When timestamps are uniformly spaced, the timestamp of the first sample can be specified and all subsequent ones calculated from the sampling rate attribute.""")
-    timestamps: Optional[TimeSeriesTimestamps] = Field(None, description="""Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time.""")
-    control: Optional[TimeSeriesControl] = Field(None, description="""Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data.""")
-    control_description: Optional[TimeSeriesControlDescription] = Field(None, description="""Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0.""")
+    timestamps: Optional[List[float]] = Field(default_factory=list, description="""Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time.""")
+    control: Optional[List[int]] = Field(default_factory=list, description="""Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data.""")
+    control_description: Optional[List[str]] = Field(default_factory=list, description="""Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0.""")
     sync: Optional[TimeSeriesSync] = Field(None, description="""Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of 'sync' are mostly for archival purposes.""")
     
 
@@ -119,36 +115,40 @@ class DfOverF(NWBDataInterface):
     """
     dF/F information about a region of interest (ROI). Storage hierarchy of dF/F should be the same as for segmentation (i.e., same names for ROIs and for image planes).
     """
-    RoiResponseSeries: List[RoiResponseSeries] = Field(default_factory=list, description="""RoiResponseSeries object(s) containing dF/F for a ROI.""")
+    name: str = Field(...)
+    roi_response_series: List[RoiResponseSeries] = Field(default_factory=list, description="""RoiResponseSeries object(s) containing dF/F for a ROI.""")
     
 
 class Fluorescence(NWBDataInterface):
     """
     Fluorescence information about a region of interest (ROI). Storage hierarchy of fluorescence should be the same as for segmentation (ie, same names for ROIs and for image planes).
     """
-    RoiResponseSeries: List[RoiResponseSeries] = Field(default_factory=list, description="""RoiResponseSeries object(s) containing fluorescence data for a ROI.""")
+    name: str = Field(...)
+    roi_response_series: List[RoiResponseSeries] = Field(default_factory=list, description="""RoiResponseSeries object(s) containing fluorescence data for a ROI.""")
     
 
 class ImageSegmentation(NWBDataInterface):
     """
     Stores pixels in an image that represent different regions of interest (ROIs) or masks. All segmentation for a given imaging plane is stored together, with storage for multiple imaging planes (masks) supported. Each ROI is stored in its own subgroup, with the ROI group containing both a 2D mask and a list of pixels that make up this mask. Segments can also be used for masking neuropil. If segmentation is allowed to change with time, a new imaging plane (or module) is required and ROI names should remain consistent between them.
     """
-    PlaneSegmentation: List[PlaneSegmentation] = Field(default_factory=list, description="""Results from image segmentation of a specific imaging plane.""")
+    name: str = Field(...)
+    plane_segmentation: List[PlaneSegmentation] = Field(default_factory=list, description="""Results from image segmentation of a specific imaging plane.""")
     
 
 class PlaneSegmentation(DynamicTable):
     """
     Results from image segmentation of a specific imaging plane.
     """
+    name: str = Field(...)
     image_mask: Optional[PlaneSegmentationImageMask] = Field(None, description="""ROI masks for each ROI. Each image mask is the size of the original imaging plane (or volume) and members of the ROI are finite non-zero.""")
     pixel_mask_index: Optional[PlaneSegmentationPixelMaskIndex] = Field(None, description="""Index into pixel_mask.""")
     pixel_mask: Optional[List[Any]] = Field(default_factory=list, description="""Pixel masks for each ROI: a list of indices and weights for the ROI. Pixel masks are concatenated and parsing of this dataset is maintained by the PlaneSegmentation""")
     voxel_mask_index: Optional[PlaneSegmentationVoxelMaskIndex] = Field(None, description="""Index into voxel_mask.""")
     voxel_mask: Optional[List[Any]] = Field(default_factory=list, description="""Voxel masks for each ROI: a list of indices and weights for the ROI. Voxel masks are concatenated and parsing of this dataset is maintained by the PlaneSegmentation""")
-    reference_images: PlaneSegmentationReferenceImages = Field(..., description="""Image stacks that the segmentation masks apply to.""")
+    reference_images: Optional[List[ImageSeries]] = Field(default_factory=list, description="""Image stacks that the segmentation masks apply to.""")
     colnames: Optional[str] = Field(None, description="""The names of the columns in this table. This should be used to specify an order to the columns.""")
     description: Optional[str] = Field(None, description="""Description of what is in this dynamic table.""")
-    id: DynamicTableId = Field(..., description="""Array of unique identifiers for the rows of this dynamic table.""")
+    id: List[int] = Field(default_factory=list, description="""Array of unique identifiers for the rows of this dynamic table.""")
     VectorData: Optional[List[VectorData]] = Field(default_factory=list, description="""Vector columns, including index columns, of this dynamic table.""")
     
 
@@ -156,6 +156,7 @@ class ImagingPlane(NWBContainer):
     """
     An imaging plane and its metadata.
     """
+    name: str = Field(...)
     description: Optional[str] = Field(None, description="""Description of the imaging plane.""")
     excitation_lambda: float = Field(..., description="""Excitation wavelength, in nm.""")
     imaging_rate: Optional[float] = Field(None, description="""Rate that images are acquired, in Hz. If the corresponding TimeSeries is present, the rate should be stored there instead.""")
@@ -165,13 +166,14 @@ class ImagingPlane(NWBContainer):
     origin_coords: Optional[ImagingPlaneOriginCoords] = Field(None, description="""Physical location of the first element of the imaging plane (0, 0) for 2-D data or (0, 0, 0) for 3-D data. See also reference_frame for what the physical location is relative to (e.g., bregma).""")
     grid_spacing: Optional[ImagingPlaneGridSpacing] = Field(None, description="""Space between pixels in (x, y) or voxels in (x, y, z) directions, in the specified unit. Assumes imaging plane is a regular grid. See also reference_frame to interpret the grid.""")
     reference_frame: Optional[str] = Field(None, description="""Describes reference frame of origin_coords and grid_spacing. For example, this can be a text description of the anatomical location and orientation of the grid defined by origin_coords and grid_spacing or the vectors needed to transform or rotate the grid to a common anatomical axis (e.g., AP/DV/ML). This field is necessary to interpret origin_coords and grid_spacing. If origin_coords and grid_spacing are not present, then this field is not required. For example, if the microscope takes 10 x 10 x 2 images, where the first value of the data matrix (index (0, 0, 0)) corresponds to (-1.2, -0.6, -2) mm relative to bregma, the spacing between pixels is 0.2 mm in x, 0.2 mm in y and 0.5 mm in z, and larger numbers in x means more anterior, larger numbers in y means more rightward, and larger numbers in z means more ventral, then enter the following -- origin_coords = (-1.2, -0.6, -2) grid_spacing = (0.2, 0.2, 0.5) reference_frame = \"Origin coordinates are relative to bregma. First dimension corresponds to anterior-posterior axis (larger index = more anterior). Second dimension corresponds to medial-lateral axis (larger index = more rightward). Third dimension corresponds to dorsal-ventral axis (larger index = more ventral).\"""")
-    OpticalChannel: List[OpticalChannel] = Field(default_factory=list, description="""An optical channel used to record from an imaging plane.""")
+    optical_channel: List[OpticalChannel] = Field(default_factory=list, description="""An optical channel used to record from an imaging plane.""")
     
 
 class OpticalChannel(NWBContainer):
     """
     An optical channel used to record from an imaging plane.
     """
+    name: str = Field(...)
     description: str = Field(..., description="""Description or other notes about the channel.""")
     emission_lambda: float = Field(..., description="""Emission wavelength for channel, in nm.""")
     
@@ -180,28 +182,31 @@ class MotionCorrection(NWBDataInterface):
     """
     An image stack where all frames are shifted (registered) to a common coordinate system, to account for movement and drift between frames. Note: each frame at each point in time is assumed to be 2-D (has only x & y dimensions).
     """
-    CorrectedImageStack: List[CorrectedImageStack] = Field(default_factory=list, description="""Reuslts from motion correction of an image stack.""")
+    name: str = Field(...)
+    corrected_image_stack: List[CorrectedImageStack] = Field(default_factory=list, description="""Reuslts from motion correction of an image stack.""")
     
 
 class CorrectedImageStack(NWBDataInterface):
     """
     Reuslts from motion correction of an image stack.
     """
-    corrected: CorrectedImageStackCorrected = Field(..., description="""Image stack with frames shifted to the common coordinates.""")
-    xy_translation: CorrectedImageStackXyTranslation = Field(..., description="""Stores the x,y delta necessary to align each frame to the common coordinates, for example, to align each frame to a reference image.""")
+    name: str = Field(...)
+    corrected: ImageSeries = Field(..., description="""Image stack with frames shifted to the common coordinates.""")
+    xy_translation: TimeSeries = Field(..., description="""Stores the x,y delta necessary to align each frame to the common coordinates, for example, to align each frame to a reference image.""")
     
 
 
-# Update forward refs
-# see https://pydantic-docs.helpmanual.io/usage/postponed_annotations/
-OnePhotonSeries.update_forward_refs()
-TwoPhotonSeries.update_forward_refs()
-RoiResponseSeries.update_forward_refs()
-DfOverF.update_forward_refs()
-Fluorescence.update_forward_refs()
-ImageSegmentation.update_forward_refs()
-PlaneSegmentation.update_forward_refs()
-ImagingPlane.update_forward_refs()
-OpticalChannel.update_forward_refs()
-MotionCorrection.update_forward_refs()
-CorrectedImageStack.update_forward_refs()
+# Model rebuild
+# see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
+OnePhotonSeries.model_rebuild()
+TwoPhotonSeries.model_rebuild()
+RoiResponseSeries.model_rebuild()
+DfOverF.model_rebuild()
+Fluorescence.model_rebuild()
+ImageSegmentation.model_rebuild()
+PlaneSegmentation.model_rebuild()
+ImagingPlane.model_rebuild()
+OpticalChannel.model_rebuild()
+MotionCorrection.model_rebuild()
+CorrectedImageStack.model_rebuild()
+    

nwb_linkml/models/core_nwb_ophys_include.py

@@ -13,33 +13,21 @@ else:
 
 from .hdmf_common_table import (
     DynamicTableRegion,
-    VectorIndex,
-    VectorData
-)
-
-from .core_nwb_image import (
-    ImageSeries
+    VectorData,
+    VectorIndex
 )
 
 from .nwb_language import (
     Arraylike
 )
 
-from .core_nwb_base import (
-    TimeSeries
-)
-
 
 metamodel_version = "None"
 version = "None"
 
-class WeakRefShimBaseModel(BaseModel):
-   __slots__ = '__weakref__'
-
-class ConfiguredBaseModel(WeakRefShimBaseModel,
+class ConfiguredBaseModel(BaseModel,
                 validate_assignment = True,
-                validate_all = True,
-                underscore_attrs_are_private = True,
+                validate_default = True,
                 extra = 'forbid',
                 arbitrary_types_allowed = True,
                 use_enum_values = True):
@@ -50,7 +38,11 @@ class TwoPhotonSeriesFieldOfView(ConfiguredBaseModel):
     """
     Width, height and depth of image, or imaged area, in meters.
     """
-    array: Optional[NDArray[Shape["2 width|height, 3 width|height|depth"], Float32]] = Field(None)
+    name: str = Field("field_of_view", const=True)
+    array: Optional[Union[
+        NDArray[Shape["2 width|height"], Float32],
+        NDArray[Shape["2 width|height, 3 width|height|depth"], Float32]
+    ]] = Field(None)
     
 
 class TwoPhotonSeriesFieldOfViewArray(Arraylike):
@@ -63,7 +55,11 @@ class RoiResponseSeriesData(ConfiguredBaseModel):
     """
     Signals from ROIs.
     """
-    array: Optional[NDArray[Shape["* num_times, * num_ROIs"], Number]] = Field(None)
+    name: str = Field("data", const=True)
+    array: Optional[Union[
+        NDArray[Shape["* num_times"], Number],
+        NDArray[Shape["* num_times, * num_ROIs"], Number]
+    ]] = Field(None)
     
 
 class RoiResponseSeriesDataArray(Arraylike):
@@ -76,51 +72,72 @@ class RoiResponseSeriesRois(DynamicTableRegion):
     """
     DynamicTableRegion referencing into an ROITable containing information on the ROIs stored in this timeseries.
     """
+    name: str = Field("rois", const=True)
     table: Optional[DynamicTable] = Field(None, description="""Reference to the DynamicTable object that this region applies to.""")
     description: Optional[str] = Field(None, description="""Description of what this table region points to.""")
-    array: Optional[NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], ]] = Field(None)
+    array: Optional[Union[
+        NDArray[Shape["* dim0"], Any],
+        NDArray[Shape["* dim0, * dim1"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], Any]
+    ]] = Field(None)
     
 
 class PlaneSegmentationImageMask(VectorData):
     """
     ROI masks for each ROI. Each image mask is the size of the original imaging plane (or volume) and members of the ROI are finite non-zero.
     """
+    name: str = Field("image_mask", const=True)
     description: Optional[str] = Field(None, description="""Description of what these vectors represent.""")
-    array: Optional[NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], ]] = Field(None)
+    array: Optional[Union[
+        NDArray[Shape["* dim0"], Any],
+        NDArray[Shape["* dim0, * dim1"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], Any]
+    ]] = Field(None)
     
 
 class PlaneSegmentationPixelMaskIndex(VectorIndex):
     """
     Index into pixel_mask.
     """
+    name: str = Field("pixel_mask_index", const=True)
     target: Optional[VectorData] = Field(None, description="""Reference to the target dataset that this index applies to.""")
     description: Optional[str] = Field(None, description="""Description of what these vectors represent.""")
-    array: Optional[NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], ]] = Field(None)
+    array: Optional[Union[
+        NDArray[Shape["* dim0"], Any],
+        NDArray[Shape["* dim0, * dim1"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], Any]
+    ]] = Field(None)
     
 
 class PlaneSegmentationVoxelMaskIndex(VectorIndex):
     """
     Index into voxel_mask.
     """
+    name: str = Field("voxel_mask_index", const=True)
     target: Optional[VectorData] = Field(None, description="""Reference to the target dataset that this index applies to.""")
     description: Optional[str] = Field(None, description="""Description of what these vectors represent.""")
-    array: Optional[NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], ]] = Field(None)
-    
-
-class PlaneSegmentationReferenceImages(ConfiguredBaseModel):
-    """
-    Image stacks that the segmentation masks apply to.
-    """
-    ImageSeries: Optional[List[ImageSeries]] = Field(default_factory=list, description="""One or more image stacks that the masks apply to (can be one-element stack).""")
+    array: Optional[Union[
+        NDArray[Shape["* dim0"], Any],
+        NDArray[Shape["* dim0, * dim1"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], Any]
+    ]] = Field(None)
     
 
 class ImagingPlaneManifold(ConfiguredBaseModel):
     """
     DEPRECATED Physical position of each pixel. 'xyz' represents the position of the pixel relative to the defined coordinate space. Deprecated in favor of origin_coords and grid_spacing.
     """
+    name: str = Field("manifold", const=True)
     conversion: Optional[float] = Field(None, description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as pixels from x = -500 to 499, y = -500 to 499 that correspond to a 2 m x 2 m range, then the 'conversion' multiplier to get from raw data acquisition pixel units to meters is 2/1000.""")
     unit: Optional[str] = Field(None, description="""Base unit of measurement for working with the data. The default value is 'meters'.""")
-    array: Optional[NDArray[Shape["* height, * width, 3 x_y_z, * depth"], Float32]] = Field(None)
+    array: Optional[Union[
+        NDArray[Shape["* height, * width, 3 x_y_z"], Float32],
+        NDArray[Shape["* height, * width, 3 x_y_z, * depth"], Float32]
+    ]] = Field(None)
     
 
 class ImagingPlaneManifoldArray(Arraylike):
@@ -135,8 +152,12 @@ class ImagingPlaneOriginCoords(ConfiguredBaseModel):
     """
     Physical location of the first element of the imaging plane (0, 0) for 2-D data or (0, 0, 0) for 3-D data. See also reference_frame for what the physical location is relative to (e.g., bregma).
     """
+    name: str = Field("origin_coords", const=True)
     unit: Optional[str] = Field(None, description="""Measurement units for origin_coords. The default value is 'meters'.""")
-    array: Optional[NDArray[Shape["2 x_y, 3 x_y_z"], Float32]] = Field(None)
+    array: Optional[Union[
+        NDArray[Shape["2 x_y"], Float32],
+        NDArray[Shape["2 x_y, 3 x_y_z"], Float32]
+    ]] = Field(None)
     
 
 class ImagingPlaneOriginCoordsArray(Arraylike):
@@ -149,8 +170,12 @@ class ImagingPlaneGridSpacing(ConfiguredBaseModel):
     """
     Space between pixels in (x, y) or voxels in (x, y, z) directions, in the specified unit. Assumes imaging plane is a regular grid. See also reference_frame to interpret the grid.
     """
+    name: str = Field("grid_spacing", const=True)
     unit: Optional[str] = Field(None, description="""Measurement units for grid_spacing. The default value is 'meters'.""")
-    array: Optional[NDArray[Shape["2 x_y, 3 x_y_z"], Float32]] = Field(None)
+    array: Optional[Union[
+        NDArray[Shape["2 x_y"], Float32],
+        NDArray[Shape["2 x_y, 3 x_y_z"], Float32]
+    ]] = Field(None)
     
 
 class ImagingPlaneGridSpacingArray(Arraylike):
@@ -159,54 +184,21 @@ class ImagingPlaneGridSpacingArray(Arraylike):
     x_y_z: Optional[float] = Field(None)
     
 
-class CorrectedImageStackCorrected(ImageSeries):
-    """
-    Image stack with frames shifted to the common coordinates.
-    """
-    data: ImageSeriesData = Field(..., description="""Binary data representing images across frames. If data are stored in an external file, this should be an empty 3D array.""")
-    dimension: Optional[ImageSeriesDimension] = Field(None, description="""Number of pixels on x, y, (and z) axes.""")
-    external_file: Optional[ImageSeriesExternalFile] = Field(None, description="""Paths to one or more external file(s). The field is only present if format='external'. This is only relevant if the image series is stored in the file system as one or more image file(s). This field should NOT be used if the image is stored in another NWB file and that file is linked to this file.""")
-    format: Optional[str] = Field(None, description="""Format of image. If this is 'external', then the attribute 'external_file' contains the path information to the image files. If this is 'raw', then the raw (single-channel) binary data is stored in the 'data' dataset. If this attribute is not present, then the default format='raw' case is assumed.""")
-    description: Optional[str] = Field(None, description="""Description of the time series.""")
-    comments: Optional[str] = Field(None, description="""Human-readable comments about the TimeSeries. This second descriptive field can be used to store additional information, or descriptive information if the primary description field is populated with a computer-readable string.""")
-    starting_time: Optional[TimeSeriesStartingTime] = Field(None, description="""Timestamp of the first sample in seconds. When timestamps are uniformly spaced, the timestamp of the first sample can be specified and all subsequent ones calculated from the sampling rate attribute.""")
-    timestamps: Optional[TimeSeriesTimestamps] = Field(None, description="""Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time.""")
-    control: Optional[TimeSeriesControl] = Field(None, description="""Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data.""")
-    control_description: Optional[TimeSeriesControlDescription] = Field(None, description="""Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0.""")
-    sync: Optional[TimeSeriesSync] = Field(None, description="""Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of 'sync' are mostly for archival purposes.""")
 
+# Model rebuild
+# see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
+TwoPhotonSeriesFieldOfView.model_rebuild()
+TwoPhotonSeriesFieldOfViewArray.model_rebuild()
+RoiResponseSeriesData.model_rebuild()
+RoiResponseSeriesDataArray.model_rebuild()
+RoiResponseSeriesRois.model_rebuild()
+PlaneSegmentationImageMask.model_rebuild()
+PlaneSegmentationPixelMaskIndex.model_rebuild()
+PlaneSegmentationVoxelMaskIndex.model_rebuild()
+ImagingPlaneManifold.model_rebuild()
+ImagingPlaneManifoldArray.model_rebuild()
+ImagingPlaneOriginCoords.model_rebuild()
+ImagingPlaneOriginCoordsArray.model_rebuild()
+ImagingPlaneGridSpacing.model_rebuild()
+ImagingPlaneGridSpacingArray.model_rebuild()
     
-class CorrectedImageStackXyTranslation(TimeSeries):
-    """
-    Stores the x,y delta necessary to align each frame to the common coordinates, for example, to align each frame to a reference image.
-    """
-    description: Optional[str] = Field(None, description="""Description of the time series.""")
-    comments: Optional[str] = Field(None, description="""Human-readable comments about the TimeSeries. This second descriptive field can be used to store additional information, or descriptive information if the primary description field is populated with a computer-readable string.""")
-    data: TimeSeriesData = Field(..., description="""Data values. Data can be in 1-D, 2-D, 3-D, or 4-D. The first dimension should always represent time. This can also be used to store binary data (e.g., image frames). This can also be a link to data stored in an external file.""")
-    starting_time: Optional[TimeSeriesStartingTime] = Field(None, description="""Timestamp of the first sample in seconds. When timestamps are uniformly spaced, the timestamp of the first sample can be specified and all subsequent ones calculated from the sampling rate attribute.""")
-    timestamps: Optional[TimeSeriesTimestamps] = Field(None, description="""Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time.""")
-    control: Optional[TimeSeriesControl] = Field(None, description="""Numerical labels that apply to each time point in data for the purpose of querying and slicing data by these values. If present, the length of this array should be the same size as the first dimension of data.""")
-    control_description: Optional[TimeSeriesControlDescription] = Field(None, description="""Description of each control value. Must be present if control is present. If present, control_description[0] should describe time points where control == 0.""")
-    sync: Optional[TimeSeriesSync] = Field(None, description="""Lab-specific time and sync information as provided directly from hardware devices and that is necessary for aligning all acquired time information to a common timebase. The timestamp array stores time in the common timebase. This group will usually only be populated in TimeSeries that are stored external to the NWB file, in files storing raw data. Once timestamp data is calculated, the contents of 'sync' are mostly for archival purposes.""")
-    
-
-
-# Update forward refs
-# see https://pydantic-docs.helpmanual.io/usage/postponed_annotations/
-TwoPhotonSeriesFieldOfView.update_forward_refs()
-TwoPhotonSeriesFieldOfViewArray.update_forward_refs()
-RoiResponseSeriesData.update_forward_refs()
-RoiResponseSeriesDataArray.update_forward_refs()
-RoiResponseSeriesRois.update_forward_refs()
-PlaneSegmentationImageMask.update_forward_refs()
-PlaneSegmentationPixelMaskIndex.update_forward_refs()
-PlaneSegmentationVoxelMaskIndex.update_forward_refs()
-PlaneSegmentationReferenceImages.update_forward_refs()
-ImagingPlaneManifold.update_forward_refs()
-ImagingPlaneManifoldArray.update_forward_refs()
-ImagingPlaneOriginCoords.update_forward_refs()
-ImagingPlaneOriginCoordsArray.update_forward_refs()
-ImagingPlaneGridSpacing.update_forward_refs()
-ImagingPlaneGridSpacingArray.update_forward_refs()
-CorrectedImageStackCorrected.update_forward_refs()
-CorrectedImageStackXyTranslation.update_forward_refs()

nwb_linkml/models/core_nwb_retinotopy.py

@@ -12,14 +12,13 @@ else:
 
 
 from .core_nwb_retinotopy_include import (
-    ImagingRetinotopyAxisDescriptions,
-    ImagingRetinotopyFocalDepthImage,
-    ImagingRetinotopyAxis2PowerMap,
-    ImagingRetinotopyVasculatureImage,
-    ImagingRetinotopyAxis2PhaseMap,
-    ImagingRetinotopyAxis1PhaseMap,
     ImagingRetinotopyAxis1PowerMap,
-    ImagingRetinotopySignMap
+    ImagingRetinotopyAxis1PhaseMap,
+    ImagingRetinotopyVasculatureImage,
+    ImagingRetinotopySignMap,
+    ImagingRetinotopyAxis2PowerMap,
+    ImagingRetinotopyAxis2PhaseMap,
+    ImagingRetinotopyFocalDepthImage
 )
 
 from .core_nwb_base import (
@@ -30,13 +29,9 @@ from .core_nwb_base import (
 metamodel_version = "None"
 version = "None"
 
-class WeakRefShimBaseModel(BaseModel):
-   __slots__ = '__weakref__'
-
-class ConfiguredBaseModel(WeakRefShimBaseModel,
+class ConfiguredBaseModel(BaseModel,
                 validate_assignment = True,
-                validate_all = True,
-                underscore_attrs_are_private = True,
+                validate_default = True,
                 extra = 'forbid',
                 arbitrary_types_allowed = True,
                 use_enum_values = True):
@@ -47,17 +42,19 @@ class ImagingRetinotopy(NWBDataInterface):
     """
     Intrinsic signal optical imaging or widefield imaging for measuring retinotopy. Stores orthogonal maps (e.g., altitude/azimuth; radius/theta) of responses to specific stimuli and a combined polarity map from which to identify visual areas. This group does not store the raw responses imaged during retinotopic mapping or the stimuli presented, but rather the resulting phase and power maps after applying a Fourier transform on the averaged responses. Note: for data consistency, all images and arrays are stored in the format [row][column] and [row, col], which equates to [y][x]. Field of view and dimension arrays may appear backward (i.e., y before x).
     """
+    name: str = Field(...)
     axis_1_phase_map: ImagingRetinotopyAxis1PhaseMap = Field(..., description="""Phase response to stimulus on the first measured axis.""")
     axis_1_power_map: Optional[ImagingRetinotopyAxis1PowerMap] = Field(None, description="""Power response on the first measured axis. Response is scaled so 0.0 is no power in the response and 1.0 is maximum relative power.""")
     axis_2_phase_map: ImagingRetinotopyAxis2PhaseMap = Field(..., description="""Phase response to stimulus on the second measured axis.""")
     axis_2_power_map: Optional[ImagingRetinotopyAxis2PowerMap] = Field(None, description="""Power response on the second measured axis. Response is scaled so 0.0 is no power in the response and 1.0 is maximum relative power.""")
-    axis_descriptions: ImagingRetinotopyAxisDescriptions = Field(..., description="""Two-element array describing the contents of the two response axis fields. Description should be something like ['altitude', 'azimuth'] or '['radius', 'theta'].""")
+    axis_descriptions: List[str] = Field(default_factory=list, description="""Two-element array describing the contents of the two response axis fields. Description should be something like ['altitude', 'azimuth'] or '['radius', 'theta'].""")
     focal_depth_image: Optional[ImagingRetinotopyFocalDepthImage] = Field(None, description="""Gray-scale image taken with same settings/parameters (e.g., focal depth, wavelength) as data collection. Array format: [rows][columns].""")
     sign_map: Optional[ImagingRetinotopySignMap] = Field(None, description="""Sine of the angle between the direction of the gradient in axis_1 and axis_2.""")
     vasculature_image: ImagingRetinotopyVasculatureImage = Field(..., description="""Gray-scale anatomical image of cortical surface. Array structure: [rows][columns]""")
     
 
 
-# Update forward refs
-# see https://pydantic-docs.helpmanual.io/usage/postponed_annotations/
-ImagingRetinotopy.update_forward_refs()
+# Model rebuild
+# see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
+ImagingRetinotopy.model_rebuild()
+    

nwb_linkml/models/core_nwb_retinotopy_include.py

@@ -19,13 +19,9 @@ from .nwb_language import (
 metamodel_version = "None"
 version = "None"
 
-class WeakRefShimBaseModel(BaseModel):
-   __slots__ = '__weakref__'
-
-class ConfiguredBaseModel(WeakRefShimBaseModel,
+class ConfiguredBaseModel(BaseModel,
                 validate_assignment = True,
-                validate_all = True,
-                underscore_attrs_are_private = True,
+                validate_default = True,
                 extra = 'forbid',
                 arbitrary_types_allowed = True,
                 use_enum_values = True):
@@ -36,6 +32,7 @@ class ImagingRetinotopyAxis1PhaseMap(ConfiguredBaseModel):
     """
     Phase response to stimulus on the first measured axis.
     """
+    name: str = Field("axis_1_phase_map", const=True)
     dimension: Optional[int] = Field(None, description="""Number of rows and columns in the image. NOTE: row, column representation is equivalent to height, width.""")
     field_of_view: Optional[float] = Field(None, description="""Size of viewing area, in meters.""")
     unit: Optional[str] = Field(None, description="""Unit that axis data is stored in (e.g., degrees).""")
@@ -44,14 +41,15 @@ class ImagingRetinotopyAxis1PhaseMap(ConfiguredBaseModel):
 
 class ImagingRetinotopyAxis1PhaseMapArray(Arraylike):
     
-    num_rows: Optional[float] = Field(None)
-    num_cols: Optional[float] = Field(None)
+    num_rows: float = Field(...)
+    num_cols: float = Field(...)
     
 
 class ImagingRetinotopyAxis1PowerMap(ConfiguredBaseModel):
     """
     Power response on the first measured axis. Response is scaled so 0.0 is no power in the response and 1.0 is maximum relative power.
     """
+    name: str = Field("axis_1_power_map", const=True)
     dimension: Optional[int] = Field(None, description="""Number of rows and columns in the image. NOTE: row, column representation is equivalent to height, width.""")
     field_of_view: Optional[float] = Field(None, description="""Size of viewing area, in meters.""")
     unit: Optional[str] = Field(None, description="""Unit that axis data is stored in (e.g., degrees).""")
@@ -60,14 +58,15 @@ class ImagingRetinotopyAxis1PowerMap(ConfiguredBaseModel):
 
 class ImagingRetinotopyAxis1PowerMapArray(Arraylike):
     
-    num_rows: Optional[float] = Field(None)
-    num_cols: Optional[float] = Field(None)
+    num_rows: float = Field(...)
+    num_cols: float = Field(...)
     
 
 class ImagingRetinotopyAxis2PhaseMap(ConfiguredBaseModel):
     """
     Phase response to stimulus on the second measured axis.
     """
+    name: str = Field("axis_2_phase_map", const=True)
     dimension: Optional[int] = Field(None, description="""Number of rows and columns in the image. NOTE: row, column representation is equivalent to height, width.""")
     field_of_view: Optional[float] = Field(None, description="""Size of viewing area, in meters.""")
     unit: Optional[str] = Field(None, description="""Unit that axis data is stored in (e.g., degrees).""")
@@ -76,14 +75,15 @@ class ImagingRetinotopyAxis2PhaseMap(ConfiguredBaseModel):
 
 class ImagingRetinotopyAxis2PhaseMapArray(Arraylike):
     
-    num_rows: Optional[float] = Field(None)
-    num_cols: Optional[float] = Field(None)
+    num_rows: float = Field(...)
+    num_cols: float = Field(...)
     
 
 class ImagingRetinotopyAxis2PowerMap(ConfiguredBaseModel):
     """
     Power response on the second measured axis. Response is scaled so 0.0 is no power in the response and 1.0 is maximum relative power.
     """
+    name: str = Field("axis_2_power_map", const=True)
     dimension: Optional[int] = Field(None, description="""Number of rows and columns in the image. NOTE: row, column representation is equivalent to height, width.""")
     field_of_view: Optional[float] = Field(None, description="""Size of viewing area, in meters.""")
     unit: Optional[str] = Field(None, description="""Unit that axis data is stored in (e.g., degrees).""")
@@ -92,21 +92,15 @@ class ImagingRetinotopyAxis2PowerMap(ConfiguredBaseModel):
 
 class ImagingRetinotopyAxis2PowerMapArray(Arraylike):
     
-    num_rows: Optional[float] = Field(None)
-    num_cols: Optional[float] = Field(None)
-    
-
-class ImagingRetinotopyAxisDescriptions(ConfiguredBaseModel):
-    """
-    Two-element array describing the contents of the two response axis fields. Description should be something like ['altitude', 'azimuth'] or '['radius', 'theta'].
-    """
-    axis_descriptions: List[str] = Field(default_factory=list, description="""Two-element array describing the contents of the two response axis fields. Description should be something like ['altitude', 'azimuth'] or '['radius', 'theta'].""")
+    num_rows: float = Field(...)
+    num_cols: float = Field(...)
     
 
 class ImagingRetinotopyFocalDepthImage(ConfiguredBaseModel):
     """
     Gray-scale image taken with same settings/parameters (e.g., focal depth, wavelength) as data collection. Array format: [rows][columns].
     """
+    name: str = Field("focal_depth_image", const=True)
     bits_per_pixel: Optional[int] = Field(None, description="""Number of bits used to represent each value. This is necessary to determine maximum (white) pixel value.""")
     dimension: Optional[int] = Field(None, description="""Number of rows and columns in the image. NOTE: row, column representation is equivalent to height, width.""")
     field_of_view: Optional[float] = Field(None, description="""Size of viewing area, in meters.""")
@@ -117,14 +111,15 @@ class ImagingRetinotopyFocalDepthImage(ConfiguredBaseModel):
 
 class ImagingRetinotopyFocalDepthImageArray(Arraylike):
     
-    num_rows: Optional[int] = Field(None)
-    num_cols: Optional[int] = Field(None)
+    num_rows: int = Field(...)
+    num_cols: int = Field(...)
     
 
 class ImagingRetinotopySignMap(ConfiguredBaseModel):
     """
     Sine of the angle between the direction of the gradient in axis_1 and axis_2.
     """
+    name: str = Field("sign_map", const=True)
     dimension: Optional[int] = Field(None, description="""Number of rows and columns in the image. NOTE: row, column representation is equivalent to height, width.""")
     field_of_view: Optional[float] = Field(None, description="""Size of viewing area, in meters.""")
     array: Optional[NDArray[Shape["* num_rows, * num_cols"], Float32]] = Field(None)
@@ -132,14 +127,15 @@ class ImagingRetinotopySignMap(ConfiguredBaseModel):
 
 class ImagingRetinotopySignMapArray(Arraylike):
     
-    num_rows: Optional[float] = Field(None)
-    num_cols: Optional[float] = Field(None)
+    num_rows: float = Field(...)
+    num_cols: float = Field(...)
     
 
 class ImagingRetinotopyVasculatureImage(ConfiguredBaseModel):
     """
     Gray-scale anatomical image of cortical surface. Array structure: [rows][columns]
     """
+    name: str = Field("vasculature_image", const=True)
     bits_per_pixel: Optional[int] = Field(None, description="""Number of bits used to represent each value. This is necessary to determine maximum (white) pixel value""")
     dimension: Optional[int] = Field(None, description="""Number of rows and columns in the image. NOTE: row, column representation is equivalent to height, width.""")
     field_of_view: Optional[float] = Field(None, description="""Size of viewing area, in meters.""")
@@ -149,25 +145,25 @@ class ImagingRetinotopyVasculatureImage(ConfiguredBaseModel):
 
 class ImagingRetinotopyVasculatureImageArray(Arraylike):
     
-    num_rows: Optional[int] = Field(None)
-    num_cols: Optional[int] = Field(None)
+    num_rows: int = Field(...)
+    num_cols: int = Field(...)
     
 
 
-# Update forward refs
-# see https://pydantic-docs.helpmanual.io/usage/postponed_annotations/
-ImagingRetinotopyAxis1PhaseMap.update_forward_refs()
-ImagingRetinotopyAxis1PhaseMapArray.update_forward_refs()
-ImagingRetinotopyAxis1PowerMap.update_forward_refs()
-ImagingRetinotopyAxis1PowerMapArray.update_forward_refs()
-ImagingRetinotopyAxis2PhaseMap.update_forward_refs()
-ImagingRetinotopyAxis2PhaseMapArray.update_forward_refs()
-ImagingRetinotopyAxis2PowerMap.update_forward_refs()
-ImagingRetinotopyAxis2PowerMapArray.update_forward_refs()
-ImagingRetinotopyAxisDescriptions.update_forward_refs()
-ImagingRetinotopyFocalDepthImage.update_forward_refs()
-ImagingRetinotopyFocalDepthImageArray.update_forward_refs()
-ImagingRetinotopySignMap.update_forward_refs()
-ImagingRetinotopySignMapArray.update_forward_refs()
-ImagingRetinotopyVasculatureImage.update_forward_refs()
-ImagingRetinotopyVasculatureImageArray.update_forward_refs()
+# Model rebuild
+# see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
+ImagingRetinotopyAxis1PhaseMap.model_rebuild()
+ImagingRetinotopyAxis1PhaseMapArray.model_rebuild()
+ImagingRetinotopyAxis1PowerMap.model_rebuild()
+ImagingRetinotopyAxis1PowerMapArray.model_rebuild()
+ImagingRetinotopyAxis2PhaseMap.model_rebuild()
+ImagingRetinotopyAxis2PhaseMapArray.model_rebuild()
+ImagingRetinotopyAxis2PowerMap.model_rebuild()
+ImagingRetinotopyAxis2PowerMapArray.model_rebuild()
+ImagingRetinotopyFocalDepthImage.model_rebuild()
+ImagingRetinotopyFocalDepthImageArray.model_rebuild()
+ImagingRetinotopySignMap.model_rebuild()
+ImagingRetinotopySignMapArray.model_rebuild()
+ImagingRetinotopyVasculatureImage.model_rebuild()
+ImagingRetinotopyVasculatureImageArray.model_rebuild()
+    

nwb_linkml/models/hdmf_common.py

@@ -15,13 +15,9 @@ else:
 metamodel_version = "None"
 version = "1.8.0"
 
-class WeakRefShimBaseModel(BaseModel):
-   __slots__ = '__weakref__'
-
-class ConfiguredBaseModel(WeakRefShimBaseModel,
+class ConfiguredBaseModel(BaseModel,
                 validate_assignment = True,
-                validate_all = True,
-                underscore_attrs_are_private = True,
+                validate_default = True,
                 extra = 'forbid',
                 arbitrary_types_allowed = True,
                 use_enum_values = True):
@@ -29,5 +25,6 @@ class ConfiguredBaseModel(WeakRefShimBaseModel,
 
 
 
-# Update forward refs
-# see https://pydantic-docs.helpmanual.io/usage/postponed_annotations/
+# Model rebuild
+# see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
+    

nwb_linkml/models/hdmf_common_base.py

@@ -15,13 +15,9 @@ else:
 metamodel_version = "None"
 version = "None"
 
-class WeakRefShimBaseModel(BaseModel):
-   __slots__ = '__weakref__'
-
-class ConfiguredBaseModel(WeakRefShimBaseModel,
+class ConfiguredBaseModel(BaseModel,
                 validate_assignment = True,
-                validate_all = True,
-                underscore_attrs_are_private = True,
+                validate_default = True,
                 extra = 'forbid',
                 arbitrary_types_allowed = True,
                 use_enum_values = True):
@@ -32,27 +28,29 @@ class Data(ConfiguredBaseModel):
     """
     An abstract data type for a dataset.
     """
-    None
+    name: str = Field(...)
     
 
 class Container(ConfiguredBaseModel):
     """
     An abstract data type for a group storing collections of data and metadata. Base type for all data and metadata containers.
     """
-    None
+    name: str = Field(...)
     
 
 class SimpleMultiContainer(Container):
     """
     A simple Container for holding onto multiple containers.
     """
+    name: str = Field(...)
     Data: Optional[List[Data]] = Field(default_factory=list, description="""Data objects held within this SimpleMultiContainer.""")
-    Container: Optional[List[Container]] = Field(default_factory=list, description="""Container objects held within this SimpleMultiContainer.""")
+    container: Optional[List[Container]] = Field(default_factory=list, description="""Container objects held within this SimpleMultiContainer.""")
     
 
 
-# Update forward refs
-# see https://pydantic-docs.helpmanual.io/usage/postponed_annotations/
-Data.update_forward_refs()
-Container.update_forward_refs()
-SimpleMultiContainer.update_forward_refs()
+# Model rebuild
+# see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
+Data.model_rebuild()
+Container.model_rebuild()
+SimpleMultiContainer.model_rebuild()
+    

nwb_linkml/models/hdmf_common_base_include.py

@@ -1,33 +0,0 @@
-from __future__ import annotations
-from datetime import datetime, date
-from enum import Enum
-from typing import List, Dict, Optional, Any, Union
-from pydantic import BaseModel as BaseModel, Field
-from nptyping import NDArray, Shape, Float, Float32, Double, Float64, LongLong, Int64, Int, Int32, Int16, Short, Int8, UInt, UInt32, UInt16, UInt8, UInt64, Number, String, Unicode, Unicode, Unicode, String, Bool, Datetime64
-import sys
-if sys.version_info >= (3, 8):
-    from typing import Literal
-else:
-    from typing_extensions import Literal
-
-
-
-metamodel_version = "None"
-version = "None"
-
-class WeakRefShimBaseModel(BaseModel):
-   __slots__ = '__weakref__'
-
-class ConfiguredBaseModel(WeakRefShimBaseModel,
-                validate_assignment = True,
-                validate_all = True,
-                underscore_attrs_are_private = True,
-                extra = 'forbid',
-                arbitrary_types_allowed = True,
-                use_enum_values = True):
-    pass
-
-
-
-# Update forward refs
-# see https://pydantic-docs.helpmanual.io/usage/postponed_annotations/

nwb_linkml/models/hdmf_common_sparse.py

@@ -11,12 +11,6 @@ else:
     from typing_extensions import Literal
 
 
-from .hdmf_common_sparse_include import (
-    CSRMatrixData,
-    CSRMatrixIndices,
-    CSRMatrixIndptr
-)
-
 from .hdmf_common_base import (
     Container
 )
@@ -25,13 +19,9 @@ from .hdmf_common_base import (
 metamodel_version = "None"
 version = "None"
 
-class WeakRefShimBaseModel(BaseModel):
-   __slots__ = '__weakref__'
-
-class ConfiguredBaseModel(WeakRefShimBaseModel,
+class ConfiguredBaseModel(BaseModel,
                 validate_assignment = True,
-                validate_all = True,
-                underscore_attrs_are_private = True,
+                validate_default = True,
                 extra = 'forbid',
                 arbitrary_types_allowed = True,
                 use_enum_values = True):
@@ -42,13 +32,15 @@ class CSRMatrix(Container):
     """
     A compressed sparse row matrix. Data are stored in the standard CSR format, where column indices for row i are stored in indices[indptr[i]:indptr[i+1]] and their corresponding values are stored in data[indptr[i]:indptr[i+1]].
     """
+    name: str = Field(...)
     shape: Optional[int] = Field(None, description="""The shape (number of rows, number of columns) of this sparse matrix.""")
-    indices: CSRMatrixIndices = Field(..., description="""The column indices.""")
-    indptr: CSRMatrixIndptr = Field(..., description="""The row index pointer.""")
-    data: CSRMatrixData = Field(..., description="""The non-zero values in the matrix.""")
+    indices: List[int] = Field(default_factory=list, description="""The column indices.""")
+    indptr: List[int] = Field(default_factory=list, description="""The row index pointer.""")
+    data: List[Any] = Field(default_factory=list, description="""The non-zero values in the matrix.""")
     
 
 
-# Update forward refs
-# see https://pydantic-docs.helpmanual.io/usage/postponed_annotations/
-CSRMatrix.update_forward_refs()
+# Model rebuild
+# see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
+CSRMatrix.model_rebuild()
+    

nwb_linkml/models/hdmf_common_sparse_include.py

@@ -1,57 +0,0 @@
-from __future__ import annotations
-from datetime import datetime, date
-from enum import Enum
-from typing import List, Dict, Optional, Any, Union
-from pydantic import BaseModel as BaseModel, Field
-from nptyping import NDArray, Shape, Float, Float32, Double, Float64, LongLong, Int64, Int, Int32, Int16, Short, Int8, UInt, UInt32, UInt16, UInt8, UInt64, Number, String, Unicode, Unicode, Unicode, String, Bool, Datetime64
-import sys
-if sys.version_info >= (3, 8):
-    from typing import Literal
-else:
-    from typing_extensions import Literal
-
-
-
-metamodel_version = "None"
-version = "None"
-
-class WeakRefShimBaseModel(BaseModel):
-   __slots__ = '__weakref__'
-
-class ConfiguredBaseModel(WeakRefShimBaseModel,
-                validate_assignment = True,
-                validate_all = True,
-                underscore_attrs_are_private = True,
-                extra = 'forbid',
-                arbitrary_types_allowed = True,
-                use_enum_values = True):
-    pass
-
-
-class CSRMatrixIndices(ConfiguredBaseModel):
-    """
-    The column indices.
-    """
-    indices: List[int] = Field(default_factory=list, description="""The column indices.""")
-    
-
-class CSRMatrixIndptr(ConfiguredBaseModel):
-    """
-    The row index pointer.
-    """
-    indptr: List[int] = Field(default_factory=list, description="""The row index pointer.""")
-    
-
-class CSRMatrixData(ConfiguredBaseModel):
-    """
-    The non-zero values in the matrix.
-    """
-    data: List[Any] = Field(default_factory=list, description="""The non-zero values in the matrix.""")
-    
-
-
-# Update forward refs
-# see https://pydantic-docs.helpmanual.io/usage/postponed_annotations/
-CSRMatrixIndices.update_forward_refs()
-CSRMatrixIndptr.update_forward_refs()
-CSRMatrixData.update_forward_refs()

nwb_linkml/models/hdmf_common_table.py

@@ -11,28 +11,23 @@ else:
     from typing_extensions import Literal
 
 
-# from .hdmf_common_table_include import (
-#     VectorDataArray,
-#     ElementIdentifiersArray,
-#     DynamicTableId
-# )
-
 from .hdmf_common_base import (
-    Container,
-    Data
+    Data,
+    Container
+)
+
+from .hdmf_common_table_include import (
+    VectorDataArray,
+    ElementIdentifiersArray
 )
 
 
 metamodel_version = "None"
 version = "None"
 
-class WeakRefShimBaseModel(BaseModel):
-   __slots__ = '__weakref__'
-
-class ConfiguredBaseModel(WeakRefShimBaseModel,
+class ConfiguredBaseModel(BaseModel,
                 validate_assignment = True,
-                validate_all = True,
-                underscore_attrs_are_private = True,
+                validate_default = True,
                 extra = 'forbid',
                 arbitrary_types_allowed = True,
                 use_enum_values = True):
@@ -43,63 +38,85 @@ class VectorData(Data):
     """
     An n-dimensional dataset representing a column of a DynamicTable. If used without an accompanying VectorIndex, first dimension is along the rows of the DynamicTable and each step along the first dimension is a cell of the larger table. VectorData can also be used to represent a ragged array if paired with a VectorIndex. This allows for storing arrays of varying length in a single cell of the DynamicTable by indexing into this VectorData. The first vector is at VectorData[0:VectorIndex[0]]. The second vector is at VectorData[VectorIndex[0]:VectorIndex[1]], and so on.
     """
+    name: str = Field(...)
     description: Optional[str] = Field(None, description="""Description of what these vectors represent.""")
-    array: Optional[NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], Any]] = Field(None)
+    array: Optional[Union[
+        NDArray[Shape["* dim0"], Any],
+        NDArray[Shape["* dim0, * dim1"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], Any]
+    ]] = Field(None)
     
 
 class VectorIndex(VectorData):
     """
     Used with VectorData to encode a ragged array. An array of indices into the first dimension of the target VectorData, and forming a map between the rows of a DynamicTable and the indices of the VectorData. The name of the VectorIndex is expected to be the name of the target VectorData object followed by \"_index\".
     """
+    name: str = Field(...)
     target: Optional[VectorData] = Field(None, description="""Reference to the target dataset that this index applies to.""")
     description: Optional[str] = Field(None, description="""Description of what these vectors represent.""")
-    array: Optional[NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], Any]] = Field(None)
+    array: Optional[Union[
+        NDArray[Shape["* dim0"], Any],
+        NDArray[Shape["* dim0, * dim1"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], Any]
+    ]] = Field(None)
     
 
 class ElementIdentifiers(Data):
     """
     A list of unique identifiers for values within a dataset, e.g. rows of a DynamicTable.
     """
+    name: str = Field(...)
     array: Optional[NDArray[Shape["* num_elements"], Int]] = Field(None)
     
 
-# class DynamicTableRegion(VectorData):
-#     """
-#     DynamicTableRegion provides a link from one table to an index or region of another. The `table` attribute is a link to another `DynamicTable`, indicating which table is referenced, and the data is int(s) indicating the row(s) (0-indexed) of the target array. `DynamicTableRegion`s can be used to associate rows with repeated meta-data without data duplication. They can also be used to create hierarchical relationships between multiple `DynamicTable`s. `DynamicTableRegion` objects may be paired with a `VectorIndex` object to create ragged references, so a single cell of a `DynamicTable` can reference many rows of another `DynamicTable`.
-#     """
-#     table: Optional[DynamicTable] = Field(None, description="""Reference to the DynamicTable object that this region applies to.""")
-#     description: Optional[str] = Field(None, description="""Description of what this table region points to.""")
-#     array: Optional[NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], Any]] = Field(None)
-#
-
-# class DynamicTable(Container):
-#     """
-#     A group containing multiple datasets that are aligned on the first dimension (Currently, this requirement if left up to APIs to check and enforce). These datasets represent different columns in the table. Apart from a column that contains unique identifiers for each row, there are no other required datasets. Users are free to add any number of custom VectorData objects (columns) here. DynamicTable also supports ragged array columns, where each element can be of a different size. To add a ragged array column, use a VectorIndex type to index the corresponding VectorData type. See documentation for VectorData and VectorIndex for more details. Unlike a compound data type, which is analogous to storing an array-of-structs, a DynamicTable can be thought of as a struct-of-arrays. This provides an alternative structure to choose from when optimizing storage for anticipated access patterns. Additionally, this type provides a way of creating a table without having to define a compound type up front. Although this convenience may be attractive, users should think carefully about how data will be accessed. DynamicTable is more appropriate for column-centric access, whereas a dataset with a compound type would be more appropriate for row-centric access. Finally, data size should also be taken into account. For small tables, performance loss may be an acceptable trade-off for the flexibility of a DynamicTable.
-#     """
-#     colnames: Optional[str] = Field(None, description="""The names of the columns in this table. This should be used to specify an order to the columns.""")
-#     description: Optional[str] = Field(None, description="""Description of what is in this dynamic table.""")
-#     id: DynamicTableId = Field(..., description="""Array of unique identifiers for the rows of this dynamic table.""")
-#     VectorData: Optional[List[VectorData]] = Field(default_factory=list, description="""Vector columns, including index columns, of this dynamic table.""")
-#
-
-# class AlignedDynamicTable(DynamicTable):
-#     """
-#     DynamicTable container that supports storing a collection of sub-tables. Each sub-table is a DynamicTable itself that is aligned with the main table by row index. I.e., all DynamicTables stored in this group MUST have the same number of rows. This type effectively defines a 2-level table in which the main data is stored in the main table implemented by this type and additional columns of the table are grouped into categories, with each category being represented by a separate DynamicTable stored within the group.
-#     """
-#     categories: Optional[str] = Field(None, description="""The names of the categories in this AlignedDynamicTable. Each category is represented by one DynamicTable stored in the parent group. This attribute should be used to specify an order of categories and the category names must match the names of the corresponding DynamicTable in the group.""")
-#     DynamicTable: Optional[List[DynamicTable]] = Field(default_factory=list, description="""A DynamicTable representing a particular category for columns in the AlignedDynamicTable parent container. The table MUST be aligned with (i.e., have the same number of rows) as all other DynamicTables stored in the AlignedDynamicTable parent container. The name of the category is given by the name of the DynamicTable and its description by the description attribute of the DynamicTable.""")
-#     colnames: Optional[str] = Field(None, description="""The names of the columns in this table. This should be used to specify an order to the columns.""")
-#     description: Optional[str] = Field(None, description="""Description of what is in this dynamic table.""")
-#     id: DynamicTableId = Field(..., description="""Array of unique identifiers for the rows of this dynamic table.""")
-#     VectorData: Optional[List[VectorData]] = Field(default_factory=list, description="""Vector columns, including index columns, of this dynamic table.""")
-#
+class DynamicTableRegion(VectorData):
+    """
+    DynamicTableRegion provides a link from one table to an index or region of another. The `table` attribute is a link to another `DynamicTable`, indicating which table is referenced, and the data is int(s) indicating the row(s) (0-indexed) of the target array. `DynamicTableRegion`s can be used to associate rows with repeated meta-data without data duplication. They can also be used to create hierarchical relationships between multiple `DynamicTable`s. `DynamicTableRegion` objects may be paired with a `VectorIndex` object to create ragged references, so a single cell of a `DynamicTable` can reference many rows of another `DynamicTable`.
+    """
+    name: str = Field(...)
+    table: Optional[DynamicTable] = Field(None, description="""Reference to the DynamicTable object that this region applies to.""")
+    description: Optional[str] = Field(None, description="""Description of what this table region points to.""")
+    array: Optional[Union[
+        NDArray[Shape["* dim0"], Any],
+        NDArray[Shape["* dim0, * dim1"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], Any]
+    ]] = Field(None)
     
 
-# Update forward refs
-# see https://pydantic-docs.helpmanual.io/usage/postponed_annotations/
-VectorData.update_forward_refs()
-VectorIndex.update_forward_refs()
-ElementIdentifiers.update_forward_refs()
-DynamicTableRegion.update_forward_refs()
-# DynamicTable.update_forward_refs()
-# AlignedDynamicTable.update_forward_refs()
+class DynamicTable(Container):
+    """
+    A group containing multiple datasets that are aligned on the first dimension (Currently, this requirement if left up to APIs to check and enforce). These datasets represent different columns in the table. Apart from a column that contains unique identifiers for each row, there are no other required datasets. Users are free to add any number of custom VectorData objects (columns) here. DynamicTable also supports ragged array columns, where each element can be of a different size. To add a ragged array column, use a VectorIndex type to index the corresponding VectorData type. See documentation for VectorData and VectorIndex for more details. Unlike a compound data type, which is analogous to storing an array-of-structs, a DynamicTable can be thought of as a struct-of-arrays. This provides an alternative structure to choose from when optimizing storage for anticipated access patterns. Additionally, this type provides a way of creating a table without having to define a compound type up front. Although this convenience may be attractive, users should think carefully about how data will be accessed. DynamicTable is more appropriate for column-centric access, whereas a dataset with a compound type would be more appropriate for row-centric access. Finally, data size should also be taken into account. For small tables, performance loss may be an acceptable trade-off for the flexibility of a DynamicTable.
+    """
+    name: str = Field(...)
+    colnames: Optional[str] = Field(None, description="""The names of the columns in this table. This should be used to specify an order to the columns.""")
+    description: Optional[str] = Field(None, description="""Description of what is in this dynamic table.""")
+    id: List[int] = Field(default_factory=list, description="""Array of unique identifiers for the rows of this dynamic table.""")
+    VectorData: Optional[List[VectorData]] = Field(default_factory=list, description="""Vector columns, including index columns, of this dynamic table.""")
+    
+
+class AlignedDynamicTable(DynamicTable):
+    """
+    DynamicTable container that supports storing a collection of sub-tables. Each sub-table is a DynamicTable itself that is aligned with the main table by row index. I.e., all DynamicTables stored in this group MUST have the same number of rows. This type effectively defines a 2-level table in which the main data is stored in the main table implemented by this type and additional columns of the table are grouped into categories, with each category being represented by a separate DynamicTable stored within the group.
+    """
+    name: str = Field(...)
+    categories: Optional[str] = Field(None, description="""The names of the categories in this AlignedDynamicTable. Each category is represented by one DynamicTable stored in the parent group. This attribute should be used to specify an order of categories and the category names must match the names of the corresponding DynamicTable in the group.""")
+    dynamic_table: Optional[List[DynamicTable]] = Field(default_factory=list, description="""A DynamicTable representing a particular category for columns in the AlignedDynamicTable parent container. The table MUST be aligned with (i.e., have the same number of rows) as all other DynamicTables stored in the AlignedDynamicTable parent container. The name of the category is given by the name of the DynamicTable and its description by the description attribute of the DynamicTable.""")
+    colnames: Optional[str] = Field(None, description="""The names of the columns in this table. This should be used to specify an order to the columns.""")
+    description: Optional[str] = Field(None, description="""Description of what is in this dynamic table.""")
+    id: List[int] = Field(default_factory=list, description="""Array of unique identifiers for the rows of this dynamic table.""")
+    VectorData: Optional[List[VectorData]] = Field(default_factory=list, description="""Vector columns, including index columns, of this dynamic table.""")
+    
+
+
+# Model rebuild
+# see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
+VectorData.model_rebuild()
+VectorIndex.model_rebuild()
+ElementIdentifiers.model_rebuild()
+DynamicTableRegion.model_rebuild()
+DynamicTable.model_rebuild()
+AlignedDynamicTable.model_rebuild()
+    

nwb_linkml/models/hdmf_common_table_include.py

@@ -11,10 +11,6 @@ else:
     from typing_extensions import Literal
 
 
-# from .hdmf_common_table import (
-#     ElementIdentifiers
-# )
-
 from .nwb_language import (
     Arraylike
 )
@@ -23,13 +19,9 @@ from .nwb_language import (
 metamodel_version = "None"
 version = "None"
 
-class WeakRefShimBaseModel(BaseModel):
-   __slots__ = '__weakref__'
-
-class ConfiguredBaseModel(WeakRefShimBaseModel,
+class ConfiguredBaseModel(BaseModel,
                 validate_assignment = True,
-                validate_all = True,
-                underscore_attrs_are_private = True,
+                validate_default = True,
                 extra = 'forbid',
                 arbitrary_types_allowed = True,
                 use_enum_values = True):
@@ -49,17 +41,9 @@ class ElementIdentifiersArray(Arraylike):
     num_elements: int = Field(...)
     
 
-# class DynamicTableId(ElementIdentifiers):
-#     """
-#     Array of unique identifiers for the rows of this dynamic table.
-#     """
-#     id: List[int] = Field(default_factory=list, description="""Array of unique identifiers for the rows of this dynamic table.""")
-#     array: Optional[NDArray[Shape["* num_elements"], Int]] = Field(None)
-#
 
+# Model rebuild
+# see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
+VectorDataArray.model_rebuild()
+ElementIdentifiersArray.model_rebuild()
     
-# Update forward refs
-# see https://pydantic-docs.helpmanual.io/usage/postponed_annotations/
-VectorDataArray.update_forward_refs()
-ElementIdentifiersArray.update_forward_refs()
-DynamicTableId.update_forward_refs()

nwb_linkml/models/hdmf_experimental.py

@@ -15,13 +15,9 @@ else:
 metamodel_version = "None"
 version = "0.5.0"
 
-class WeakRefShimBaseModel(BaseModel):
-   __slots__ = '__weakref__'
-
-class ConfiguredBaseModel(WeakRefShimBaseModel,
+class ConfiguredBaseModel(BaseModel,
                 validate_assignment = True,
-                validate_all = True,
-                underscore_attrs_are_private = True,
+                validate_default = True,
                 extra = 'forbid',
                 arbitrary_types_allowed = True,
                 use_enum_values = True):
@@ -29,5 +25,6 @@ class ConfiguredBaseModel(WeakRefShimBaseModel,
 
 
 
-# Update forward refs
-# see https://pydantic-docs.helpmanual.io/usage/postponed_annotations/
+# Model rebuild
+# see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
+    

nwb_linkml/models/hdmf_experimental_experimental.py

@@ -19,13 +19,9 @@ from .hdmf_common_table import (
 metamodel_version = "None"
 version = "None"
 
-class WeakRefShimBaseModel(BaseModel):
-   __slots__ = '__weakref__'
-
-class ConfiguredBaseModel(WeakRefShimBaseModel,
+class ConfiguredBaseModel(BaseModel,
                 validate_assignment = True,
-                validate_all = True,
-                underscore_attrs_are_private = True,
+                validate_default = True,
                 extra = 'forbid',
                 arbitrary_types_allowed = True,
                 use_enum_values = True):
@@ -36,12 +32,19 @@ class EnumData(VectorData):
     """
     Data that come from a fixed set of values. A data value of i corresponds to the i-th value in the VectorData referenced by the 'elements' attribute.
     """
+    name: str = Field(...)
     elements: Optional[VectorData] = Field(None, description="""Reference to the VectorData object that contains the enumerable elements""")
     description: Optional[str] = Field(None, description="""Description of what these vectors represent.""")
-    array: Optional[NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], ]] = Field(None)
+    array: Optional[Union[
+        NDArray[Shape["* dim0"], Any],
+        NDArray[Shape["* dim0, * dim1"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2"], Any],
+        NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], Any]
+    ]] = Field(None)
     
 
 
-# Update forward refs
-# see https://pydantic-docs.helpmanual.io/usage/postponed_annotations/
-EnumData.update_forward_refs()
+# Model rebuild
+# see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
+EnumData.model_rebuild()
+    

nwb_linkml/models/hdmf_experimental_experimental_include.py

@@ -1,33 +0,0 @@
-from __future__ import annotations
-from datetime import datetime, date
-from enum import Enum
-from typing import List, Dict, Optional, Any, Union
-from pydantic import BaseModel as BaseModel, Field
-from nptyping import NDArray, Shape, Float, Float32, Double, Float64, LongLong, Int64, Int, Int32, Int16, Short, Int8, UInt, UInt32, UInt16, UInt8, UInt64, Number, String, Unicode, Unicode, Unicode, String, Bool, Datetime64
-import sys
-if sys.version_info >= (3, 8):
-    from typing import Literal
-else:
-    from typing_extensions import Literal
-
-
-
-metamodel_version = "None"
-version = "None"
-
-class WeakRefShimBaseModel(BaseModel):
-   __slots__ = '__weakref__'
-
-class ConfiguredBaseModel(WeakRefShimBaseModel,
-                validate_assignment = True,
-                validate_all = True,
-                underscore_attrs_are_private = True,
-                extra = 'forbid',
-                arbitrary_types_allowed = True,
-                use_enum_values = True):
-    pass
-
-
-
-# Update forward refs
-# see https://pydantic-docs.helpmanual.io/usage/postponed_annotations/

nwb_linkml/models/hdmf_experimental_resources.py

@@ -15,26 +15,13 @@ from .hdmf_common_base import (
     Container
 )
 
-from .hdmf_experimental_resources_include import (
-    HERDObjectKeys,
-    HERDObjects,
-    HERDEntities,
-    HERDKeys,
-    HERDFiles,
-    HERDEntityKeys
-)
-
 
 metamodel_version = "None"
 version = "None"
 
-class WeakRefShimBaseModel(BaseModel):
-   __slots__ = '__weakref__'
-
-class ConfiguredBaseModel(WeakRefShimBaseModel,
+class ConfiguredBaseModel(BaseModel,
                 validate_assignment = True,
-                validate_all = True,
-                underscore_attrs_are_private = True,
+                validate_default = True,
                 extra = 'forbid',
                 arbitrary_types_allowed = True,
                 use_enum_values = True):
@@ -45,15 +32,17 @@ class HERD(Container):
     """
     HDMF External Resources Data Structure. A set of six tables for tracking external resource references in a file or across multiple files.
     """
-    keys: HERDKeys = Field(<built-in method keys of dict object at 0x10ab5b600>, description="""A table for storing user terms that are used to refer to external resources.""")
-    files: HERDFiles = Field(..., description="""A table for storing object ids of files used in external resources.""")
-    entities: HERDEntities = Field(..., description="""A table for mapping user terms (i.e., keys) to resource entities.""")
-    objects: HERDObjects = Field(..., description="""A table for identifying which objects in a file contain references to external resources.""")
-    object_keys: HERDObjectKeys = Field(..., description="""A table for identifying which objects use which keys.""")
-    entity_keys: HERDEntityKeys = Field(..., description="""A table for identifying which keys use which entity.""")
+    name: str = Field(...)
+    keys: List[Any] = Field(default_factory=list, description="""A table for storing user terms that are used to refer to external resources.""")
+    files: List[Any] = Field(default_factory=list, description="""A table for storing object ids of files used in external resources.""")
+    entities: List[Any] = Field(default_factory=list, description="""A table for mapping user terms (i.e., keys) to resource entities.""")
+    objects: List[Any] = Field(default_factory=list, description="""A table for identifying which objects in a file contain references to external resources.""")
+    object_keys: List[Any] = Field(default_factory=list, description="""A table for identifying which objects use which keys.""")
+    entity_keys: List[Any] = Field(default_factory=list, description="""A table for identifying which keys use which entity.""")
     
 
 
-# Update forward refs
-# see https://pydantic-docs.helpmanual.io/usage/postponed_annotations/
-HERD.update_forward_refs()
+# Model rebuild
+# see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
+HERD.model_rebuild()
+    

nwb_linkml/models/hdmf_experimental_resources_include.py

@@ -1,85 +0,0 @@
-from __future__ import annotations
-from datetime import datetime, date
-from enum import Enum
-from typing import List, Dict, Optional, Any, Union
-from pydantic import BaseModel as BaseModel, Field
-from nptyping import NDArray, Shape, Float, Float32, Double, Float64, LongLong, Int64, Int, Int32, Int16, Short, Int8, UInt, UInt32, UInt16, UInt8, UInt64, Number, String, Unicode, Unicode, Unicode, String, Bool, Datetime64
-import sys
-if sys.version_info >= (3, 8):
-    from typing import Literal
-else:
-    from typing_extensions import Literal
-
-
-from .hdmf_common_base import (
-    Data
-)
-
-
-metamodel_version = "None"
-version = "None"
-
-class WeakRefShimBaseModel(BaseModel):
-   __slots__ = '__weakref__'
-
-class ConfiguredBaseModel(WeakRefShimBaseModel,
-                validate_assignment = True,
-                validate_all = True,
-                underscore_attrs_are_private = True,
-                extra = 'forbid',
-                arbitrary_types_allowed = True,
-                use_enum_values = True):
-    pass
-
-
-class HERDKeys(Data):
-    """
-    A table for storing user terms that are used to refer to external resources.
-    """
-    keys: List[Any] = Field(default_factory=list, description="""A table for storing user terms that are used to refer to external resources.""")
-    
-
-class HERDFiles(Data):
-    """
-    A table for storing object ids of files used in external resources.
-    """
-    files: List[Any] = Field(default_factory=list, description="""A table for storing object ids of files used in external resources.""")
-    
-
-class HERDEntities(Data):
-    """
-    A table for mapping user terms (i.e., keys) to resource entities.
-    """
-    entities: List[Any] = Field(default_factory=list, description="""A table for mapping user terms (i.e., keys) to resource entities.""")
-    
-
-class HERDObjects(Data):
-    """
-    A table for identifying which objects in a file contain references to external resources.
-    """
-    objects: List[Any] = Field(default_factory=list, description="""A table for identifying which objects in a file contain references to external resources.""")
-    
-
-class HERDObjectKeys(Data):
-    """
-    A table for identifying which objects use which keys.
-    """
-    object_keys: List[Any] = Field(default_factory=list, description="""A table for identifying which objects use which keys.""")
-    
-
-class HERDEntityKeys(Data):
-    """
-    A table for identifying which keys use which entity.
-    """
-    entity_keys: List[Any] = Field(default_factory=list, description="""A table for identifying which keys use which entity.""")
-    
-
-
-# Update forward refs
-# see https://pydantic-docs.helpmanual.io/usage/postponed_annotations/
-HERDKeys.update_forward_refs()
-HERDFiles.update_forward_refs()
-HERDEntities.update_forward_refs()
-HERDObjects.update_forward_refs()
-HERDObjectKeys.update_forward_refs()
-HERDEntityKeys.update_forward_refs()

nwb_linkml/models/nwb_language.py

@@ -15,13 +15,9 @@ else:
 metamodel_version = "None"
 version = "None"
 
-class WeakRefShimBaseModel(BaseModel):
-   __slots__ = '__weakref__'
-
-class ConfiguredBaseModel(WeakRefShimBaseModel,
+class ConfiguredBaseModel(BaseModel,
                 validate_assignment = True,
-                validate_all = True,
-                underscore_attrs_are_private = True,
+                validate_default = True,
                 extra = 'forbid',
                 arbitrary_types_allowed = True,
                 use_enum_values = True):
@@ -36,6 +32,7 @@ class Arraylike(ConfiguredBaseModel):
     
 
 
-# Update forward refs
-# see https://pydantic-docs.helpmanual.io/usage/postponed_annotations/
-Arraylike.update_forward_refs()
+# Model rebuild
+# see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
+Arraylike.model_rebuild()
+    

nwb_linkml/namespaces.py

@@ -121,7 +121,7 @@ class GitRepo:
 
         # Check that the remote matches
         if self.remote.strip('.git') != self.namespace.repository:
-            warnings.warn('Repository exists, but has the wrong remote URL')
+            warnings.warn(f'Repository exists, but has the wrong remote URL.\nExpected: {self.namespace.repository}\nGot:{self.remote.strip(".git")}')
             return False
 
         # otherwise we're good

nwb_linkml/schema/core.nwb.base.include.yaml

@@ -46,6 +46,12 @@ classes:
       should always represent time. This can also be used to store binary data (e.g.,
       image frames). This can also be a link to data stored in an external file.
     attributes:
+      name:
+        name: name
+        ifabsent: string(data)
+        range: string
+        required: true
+        equals_string: data
       conversion:
         name: conversion
         description: Scalar to multiply each element in data to convert it to the
@@ -120,6 +126,12 @@ classes:
       spaced, the timestamp of the first sample can be specified and all subsequent
       ones calculated from the sampling rate attribute.
     attributes:
+      name:
+        name: name
+        ifabsent: string(starting_time)
+        range: string
+        required: true
+        equals_string: starting_time
       rate:
         name: rate
         description: Sampling rate, in Hz.
@@ -128,54 +140,6 @@ classes:
         name: unit
         description: Unit of measurement for time, which is fixed to 'seconds'.
         range: text
-  TimeSeries__timestamps:
-    name: TimeSeries__timestamps
-    description: Timestamps for samples stored in data, in seconds, relative to the
-      common experiment master-clock stored in NWBFile.timestamps_reference_time.
-    attributes:
-      interval:
-        name: interval
-        description: Value is '1'
-        range: int32
-      unit:
-        name: unit
-        description: Unit of measurement for timestamps, which is fixed to 'seconds'.
-        range: text
-      timestamps:
-        name: timestamps
-        description: Timestamps for samples stored in data, in seconds, relative to
-          the common experiment master-clock stored in NWBFile.timestamps_reference_time.
-        multivalued: true
-        range: float64
-        required: false
-  TimeSeries__control:
-    name: TimeSeries__control
-    description: Numerical labels that apply to each time point in data for the purpose
-      of querying and slicing data by these values. If present, the length of this
-      array should be the same size as the first dimension of data.
-    attributes:
-      control:
-        name: control
-        description: Numerical labels that apply to each time point in data for the
-          purpose of querying and slicing data by these values. If present, the length
-          of this array should be the same size as the first dimension of data.
-        multivalued: true
-        range: uint8
-        required: false
-  TimeSeries__control_description:
-    name: TimeSeries__control_description
-    description: Description of each control value. Must be present if control is
-      present. If present, control_description[0] should describe time points where
-      control == 0.
-    attributes:
-      control_description:
-        name: control_description
-        description: Description of each control value. Must be present if control
-          is present. If present, control_description[0] should describe time points
-          where control == 0.
-        multivalued: true
-        range: text
-        required: false
   TimeSeries__sync:
     name: TimeSeries__sync
     description: Lab-specific time and sync information as provided directly from
@@ -184,9 +148,23 @@ classes:
       This group will usually only be populated in TimeSeries that are stored external
       to the NWB file, in files storing raw data. Once timestamp data is calculated,
       the contents of 'sync' are mostly for archival purposes.
+    attributes:
+      name:
+        name: name
+        ifabsent: string(sync)
+        range: string
+        required: true
+        equals_string: sync
   Images__order_of_images:
     name: Images__order_of_images
     description: Ordered dataset of references to Image objects stored in the parent
       group. Each Image object in the Images group should be stored once and only
       once, so the dataset should have the same length as the number of images.
     is_a: ImageReferences
+    attributes:
+      name:
+        name: name
+        ifabsent: string(order_of_images)
+        range: string
+        required: true
+        equals_string: order_of_images

nwb_linkml/schema/core.nwb.base.yaml

@@ -12,12 +12,24 @@ classes:
     name: NWBData
     description: An abstract data type for a dataset.
     is_a: Data
+    attributes:
+      name:
+        name: name
+        range: string
+        required: true
+    tree_root: true
   TimeSeriesReferenceVectorData:
     name: TimeSeriesReferenceVectorData
     description: Column storing references to a TimeSeries (rows). For each TimeSeries
       this VectorData column stores the start_index and count to indicate the range
       in time to be selected as well as an object reference to the TimeSeries.
     is_a: VectorData
+    attributes:
+      name:
+        name: name
+        range: string
+        required: true
+    tree_root: true
   Image:
     name: Image
     description: An abstract data type for an image. Shape can be 2-D (x, y), or 3-D
@@ -25,6 +37,10 @@ classes:
       b)) or (x, y, (r, g, b, a)).
     is_a: NWBData
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       resolution:
         name: resolution
         description: Pixel resolution of the image, in pixels per centimeter.
@@ -36,29 +52,51 @@ classes:
       array:
         name: array
         range: Image__Array
+    tree_root: true
   ImageReferences:
     name: ImageReferences
     description: Ordered dataset of references to Image objects.
     is_a: NWBData
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       array:
         name: array
         range: ImageReferences__Array
+    tree_root: true
   NWBContainer:
     name: NWBContainer
     description: An abstract data type for a generic container storing collections
       of data and metadata. Base type for all data and metadata containers.
     is_a: Container
+    attributes:
+      name:
+        name: name
+        range: string
+        required: true
+    tree_root: true
   NWBDataInterface:
     name: NWBDataInterface
     description: An abstract data type for a generic container storing collections
       of data, as opposed to metadata.
     is_a: NWBContainer
+    attributes:
+      name:
+        name: name
+        range: string
+        required: true
+    tree_root: true
   TimeSeries:
     name: TimeSeries
     description: General purpose time series.
     is_a: NWBDataInterface
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       description:
         name: description
         description: Description of the time series.
@@ -90,24 +128,24 @@ classes:
         name: timestamps
         description: Timestamps for samples stored in data, in seconds, relative to
           the common experiment master-clock stored in NWBFile.timestamps_reference_time.
-        multivalued: false
-        range: TimeSeries__timestamps
+        multivalued: true
+        range: float64
         required: false
       control:
         name: control
         description: Numerical labels that apply to each time point in data for the
           purpose of querying and slicing data by these values. If present, the length
           of this array should be the same size as the first dimension of data.
-        multivalued: false
-        range: TimeSeries__control
+        multivalued: true
+        range: uint8
         required: false
       control_description:
         name: control_description
         description: Description of each control value. Must be present if control
           is present. If present, control_description[0] should describe time points
           where control == 0.
-        multivalued: false
-        range: TimeSeries__control_description
+        multivalued: true
+        range: text
         required: false
       sync:
         name: sync
@@ -120,27 +158,33 @@ classes:
         multivalued: false
         range: TimeSeries__sync
         required: false
+    tree_root: true
   ProcessingModule:
     name: ProcessingModule
     description: A collection of processed data.
     is_a: NWBContainer
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       description:
         name: description
         description: Description of this collection of processed data.
         range: text
-      NWBDataInterface:
-        name: NWBDataInterface
+      nwb_data_interface:
+        name: nwb_data_interface
         description: Data objects stored in this collection.
         multivalued: true
         range: NWBDataInterface
         required: false
-      DynamicTable:
-        name: DynamicTable
+      dynamic_table:
+        name: dynamic_table
         description: Tables stored in this collection.
         multivalued: true
         range: DynamicTable
         required: false
+    tree_root: true
   Images:
     name: Images
     description: A collection of images with an optional way to specify the order
@@ -148,6 +192,10 @@ classes:
       if the images are referenced by index, e.g., from an IndexSeries.
     is_a: NWBDataInterface
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       description:
         name: description
         description: Description of this collection of images.
@@ -167,3 +215,4 @@ classes:
         multivalued: false
         range: Images__order_of_images
         required: false
+    tree_root: true

nwb_linkml/schema/core.nwb.behavior.include.yaml

@@ -13,6 +13,12 @@ classes:
     description: 1-D or 2-D array storing position or direction relative to some reference
       frame.
     attributes:
+      name:
+        name: name
+        ifabsent: string(data)
+        range: string
+        required: true
+        equals_string: data
       unit:
         name: unit
         description: Base unit of measurement for working with the data. The default

nwb_linkml/schema/core.nwb.behavior.yaml

@@ -21,6 +21,10 @@ classes:
       SpatialSeries values.'
     is_a: TimeSeries
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       data:
         name: data
         description: 1-D or 2-D array storing position or direction relative to some
@@ -34,6 +38,7 @@ classes:
         multivalued: false
         range: text
         required: false
+    tree_root: true
   BehavioralEpochs:
     name: BehavioralEpochs
     description: TimeSeries for storing behavioral epochs.  The objective of this
@@ -50,58 +55,83 @@ classes:
       events. BehavioralTimeSeries is for continuous data.
     is_a: NWBDataInterface
     attributes:
-      IntervalSeries:
-        name: IntervalSeries
+      name:
+        name: name
+        range: string
+        required: true
+      interval_series:
+        name: interval_series
         description: IntervalSeries object containing start and stop times of epochs.
         multivalued: true
         range: IntervalSeries
         required: false
+    tree_root: true
   BehavioralEvents:
     name: BehavioralEvents
     description: TimeSeries for storing behavioral events. See description of <a href="#BehavioralEpochs">BehavioralEpochs</a>
       for more details.
     is_a: NWBDataInterface
     attributes:
-      TimeSeries:
-        name: TimeSeries
+      name:
+        name: name
+        range: string
+        required: true
+      time_series:
+        name: time_series
         description: TimeSeries object containing behavioral events.
         multivalued: true
         range: TimeSeries
         required: false
+    tree_root: true
   BehavioralTimeSeries:
     name: BehavioralTimeSeries
     description: TimeSeries for storing Behavoioral time series data. See description
       of <a href="#BehavioralEpochs">BehavioralEpochs</a> for more details.
     is_a: NWBDataInterface
     attributes:
-      TimeSeries:
-        name: TimeSeries
+      name:
+        name: name
+        range: string
+        required: true
+      time_series:
+        name: time_series
         description: TimeSeries object containing continuous behavioral data.
         multivalued: true
         range: TimeSeries
         required: false
+    tree_root: true
   PupilTracking:
     name: PupilTracking
     description: Eye-tracking data, representing pupil size.
     is_a: NWBDataInterface
     attributes:
-      TimeSeries:
-        name: TimeSeries
+      name:
+        name: name
+        range: string
+        required: true
+      time_series:
+        name: time_series
         description: TimeSeries object containing time series data on pupil size.
         multivalued: true
         range: TimeSeries
         required: true
+    tree_root: true
   EyeTracking:
     name: EyeTracking
     description: Eye-tracking data, representing direction of gaze.
     is_a: NWBDataInterface
     attributes:
-      SpatialSeries:
-        name: SpatialSeries
+      name:
+        name: name
+        range: string
+        required: true
+      spatial_series:
+        name: spatial_series
         description: SpatialSeries object containing data measuring direction of gaze.
         multivalued: true
         range: SpatialSeries
         required: false
+    tree_root: true
   CompassDirection:
     name: CompassDirection
     description: With a CompassDirection interface, a module publishes a SpatialSeries
@@ -111,20 +141,30 @@ classes:
       be radians or degrees.
     is_a: NWBDataInterface
     attributes:
-      SpatialSeries:
-        name: SpatialSeries
+      name:
+        name: name
+        range: string
+        required: true
+      spatial_series:
+        name: spatial_series
         description: SpatialSeries object containing direction of gaze travel.
         multivalued: true
         range: SpatialSeries
         required: false
+    tree_root: true
   Position:
     name: Position
     description: Position data, whether along the x, x/y or x/y/z axis.
     is_a: NWBDataInterface
     attributes:
-      SpatialSeries:
-        name: SpatialSeries
+      name:
+        name: name
+        range: string
+        required: true
+      spatial_series:
+        name: spatial_series
         description: SpatialSeries object containing position data.
         multivalued: true
         range: SpatialSeries
         required: true
+    tree_root: true

nwb_linkml/schema/core.nwb.device.include.yaml

@@ -1,8 +0,0 @@
-name: core.nwb.device.include
-id: core.nwb.device.include
-imports:
-- core.nwb.base
-- nwb.language
-- core.nwb.device.include
-- core.nwb.device
-default_prefix: core.nwb.device.include/

nwb_linkml/schema/core.nwb.device.yaml

@@ -3,7 +3,6 @@ id: core.nwb.device
 imports:
 - core.nwb.base
 - nwb.language
-- core.nwb.device.include
 - core.nwb.device
 default_prefix: core.nwb.device/
 classes:
@@ -13,6 +12,10 @@ classes:
       electrode, microscope.
     is_a: NWBContainer
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       description:
         name: description
         description: Description of the device (e.g., model, firmware version, processing
@@ -22,3 +25,4 @@ classes:
         name: manufacturer
         description: The name of the manufacturer of the device.
         range: text
+    tree_root: true

nwb_linkml/schema/core.nwb.ecephys.include.yaml

@@ -13,6 +13,12 @@ classes:
     name: ElectricalSeries__data
     description: Recorded voltage data.
     attributes:
+      name:
+        name: name
+        ifabsent: string(data)
+        range: string
+        required: true
+        equals_string: data
       unit:
         name: unit
         description: Base unit of measurement for working with the data. This value
@@ -44,41 +50,23 @@ classes:
     description: DynamicTableRegion pointer to the electrodes that this time series
       was generated from.
     is_a: DynamicTableRegion
-  ElectricalSeries__channel_conversion:
-    name: ElectricalSeries__channel_conversion
-    description: Channel-specific conversion factor. Multiply the data in the 'data'
-      dataset by these values along the channel axis (as indicated by axis attribute)
-      AND by the global conversion factor in the 'conversion' attribute of 'data'
-      to get the data values in Volts, i.e, data in Volts = data * data.conversion
-      * channel_conversion. This approach allows for both global and per-channel data
-      conversion factors needed to support the storage of electrical recordings as
-      native values generated by data acquisition systems. If this dataset is not
-      present, then there is no channel-specific conversion factor, i.e. it is 1 for
-      all channels.
     attributes:
-      axis:
-        name: axis
-        description: The zero-indexed axis of the 'data' dataset that the channel-specific
-          conversion factor corresponds to. This value is fixed to 1.
-        range: int32
-      channel_conversion:
-        name: channel_conversion
-        description: Channel-specific conversion factor. Multiply the data in the
-          'data' dataset by these values along the channel axis (as indicated by axis
-          attribute) AND by the global conversion factor in the 'conversion' attribute
-          of 'data' to get the data values in Volts, i.e, data in Volts = data * data.conversion
-          * channel_conversion. This approach allows for both global and per-channel
-          data conversion factors needed to support the storage of electrical recordings
-          as native values generated by data acquisition systems. If this dataset
-          is not present, then there is no channel-specific conversion factor, i.e.
-          it is 1 for all channels.
-        multivalued: true
-        range: float32
-        required: false
+      name:
+        name: name
+        ifabsent: string(electrodes)
+        range: string
+        required: true
+        equals_string: electrodes
   SpikeEventSeries__data:
     name: SpikeEventSeries__data
     description: Spike waveforms.
     attributes:
+      name:
+        name: name
+        ifabsent: string(data)
+        range: string
+        required: true
+        equals_string: data
       unit:
         name: unit
         description: Unit of measurement for waveforms, which is fixed to 'volts'.
@@ -102,45 +90,16 @@ classes:
         name: num_channels
         range: numeric
         required: false
-  SpikeEventSeries__timestamps:
-    name: SpikeEventSeries__timestamps
-    description: Timestamps for samples stored in data, in seconds, relative to the
-      common experiment master-clock stored in NWBFile.timestamps_reference_time.
-      Timestamps are required for the events. Unlike for TimeSeries, timestamps are
-      required for SpikeEventSeries and are thus re-specified here.
-    attributes:
-      interval:
-        name: interval
-        description: Value is '1'
-        range: int32
-      unit:
-        name: unit
-        description: Unit of measurement for timestamps, which is fixed to 'seconds'.
-        range: text
-      timestamps:
-        name: timestamps
-        description: Timestamps for samples stored in data, in seconds, relative to
-          the common experiment master-clock stored in NWBFile.timestamps_reference_time.
-          Timestamps are required for the events. Unlike for TimeSeries, timestamps
-          are required for SpikeEventSeries and are thus re-specified here.
-        multivalued: true
-        range: float64
-        required: true
-  FeatureExtraction__description:
-    name: FeatureExtraction__description
-    description: Description of features (eg, ''PC1'') for each of the extracted features.
-    attributes:
-      description:
-        name: description
-        description: Description of features (eg, ''PC1'') for each of the extracted
-          features.
-        multivalued: true
-        range: text
-        required: true
   FeatureExtraction__features:
     name: FeatureExtraction__features
     description: Multi-dimensional array of features extracted from each event.
     attributes:
+      name:
+        name: name
+        ifabsent: string(features)
+        range: string
+        required: true
+        equals_string: features
       array:
         name: array
         range: FeatureExtraction__features__Array
@@ -151,60 +110,27 @@ classes:
       num_events:
         name: num_events
         range: float32
-        required: false
+        required: true
       num_channels:
         name: num_channels
         range: float32
-        required: false
+        required: true
       num_features:
         name: num_features
         range: float32
-        required: false
-  FeatureExtraction__times:
-    name: FeatureExtraction__times
-    description: Times of events that features correspond to (can be a link).
-    attributes:
-      times:
-        name: times
-        description: Times of events that features correspond to (can be a link).
-        multivalued: true
-        range: float64
         required: true
   FeatureExtraction__electrodes:
     name: FeatureExtraction__electrodes
     description: DynamicTableRegion pointer to the electrodes that this time series
       was generated from.
     is_a: DynamicTableRegion
-  EventDetection__source_idx:
-    name: EventDetection__source_idx
-    description: Indices (zero-based) into source ElectricalSeries::data array corresponding
-      to time of event. ''description'' should define what is meant by time of event
-      (e.g., .25 ms before action potential peak, zero-crossing time, etc). The index
-      points to each event from the raw data.
     attributes:
-      source_idx:
-        name: source_idx
-        description: Indices (zero-based) into source ElectricalSeries::data array
-          corresponding to time of event. ''description'' should define what is meant
-          by time of event (e.g., .25 ms before action potential peak, zero-crossing
-          time, etc). The index points to each event from the raw data.
-        multivalued: true
-        range: int32
-        required: true
-  EventDetection__times:
-    name: EventDetection__times
-    description: Timestamps of events, in seconds.
-    attributes:
-      unit:
-        name: unit
-        description: Unit of measurement for event times, which is fixed to 'seconds'.
-        range: text
-      times:
-        name: times
-        description: Timestamps of events, in seconds.
-        multivalued: true
-        range: float64
+      name:
+        name: name
+        ifabsent: string(electrodes)
+        range: string
         required: true
+        equals_string: electrodes
   ClusterWaveforms__waveform_mean:
     name: ClusterWaveforms__waveform_mean
     description: The mean waveform for each cluster, using the same indices for each
@@ -212,6 +138,12 @@ classes:
       is in array slot [3]). Waveforms corresponding to gaps in cluster sequence should
       be empty (e.g., zero- filled)
     attributes:
+      name:
+        name: name
+        ifabsent: string(waveform_mean)
+        range: string
+        required: true
+        equals_string: waveform_mean
       array:
         name: array
         range: ClusterWaveforms__waveform_mean__Array
@@ -222,16 +154,22 @@ classes:
       num_clusters:
         name: num_clusters
         range: float32
-        required: false
+        required: true
       num_samples:
         name: num_samples
         range: float32
-        required: false
+        required: true
   ClusterWaveforms__waveform_sd:
     name: ClusterWaveforms__waveform_sd
     description: Stdev of waveforms for each cluster, using the same indices as in
       mean
     attributes:
+      name:
+        name: name
+        ifabsent: string(waveform_sd)
+        range: string
+        required: true
+        equals_string: waveform_sd
       array:
         name: array
         range: ClusterWaveforms__waveform_sd__Array
@@ -242,42 +180,8 @@ classes:
       num_clusters:
         name: num_clusters
         range: float32
-        required: false
+        required: true
       num_samples:
         name: num_samples
         range: float32
-        required: false
-  Clustering__num:
-    name: Clustering__num
-    description: Cluster number of each event
-    attributes:
-      num:
-        name: num
-        description: Cluster number of each event
-        multivalued: true
-        range: int32
-        required: true
-  Clustering__peak_over_rms:
-    name: Clustering__peak_over_rms
-    description: Maximum ratio of waveform peak to RMS on any channel in the cluster
-      (provides a basic clustering metric).
-    attributes:
-      peak_over_rms:
-        name: peak_over_rms
-        description: Maximum ratio of waveform peak to RMS on any channel in the cluster
-          (provides a basic clustering metric).
-        multivalued: true
-        range: float32
-        required: true
-  Clustering__times:
-    name: Clustering__times
-    description: Times of clustered events, in seconds. This may be a link to times
-      field in associated FeatureExtraction module.
-    attributes:
-      times:
-        name: times
-        description: Times of clustered events, in seconds. This may be a link to
-          times field in associated FeatureExtraction module.
-        multivalued: true
-        range: float64
         required: true

nwb_linkml/schema/core.nwb.ecephys.yaml

@@ -17,6 +17,10 @@ classes:
       channels.
     is_a: TimeSeries
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       filtering:
         name: filtering
         description: Filtering applied to all channels of the data. For example, if
@@ -51,9 +55,10 @@ classes:
           as native values generated by data acquisition systems. If this dataset
           is not present, then there is no channel-specific conversion factor, i.e.
           it is 1 for all channels.
-        multivalued: false
-        range: ElectricalSeries__channel_conversion
+        multivalued: true
+        range: float32
         required: false
+    tree_root: true
   SpikeEventSeries:
     name: SpikeEventSeries
     description: 'Stores snapshots/snippets of recorded spike events (i.e., threshold
@@ -66,6 +71,10 @@ classes:
       [num samples] for single electrode).'
     is_a: ElectricalSeries
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       data:
         name: data
         description: Spike waveforms.
@@ -78,21 +87,26 @@ classes:
           the common experiment master-clock stored in NWBFile.timestamps_reference_time.
           Timestamps are required for the events. Unlike for TimeSeries, timestamps
           are required for SpikeEventSeries and are thus re-specified here.
-        multivalued: false
-        range: SpikeEventSeries__timestamps
+        multivalued: true
+        range: float64
         required: true
+    tree_root: true
   FeatureExtraction:
     name: FeatureExtraction
     description: Features, such as PC1 and PC2, that are extracted from signals stored
       in a SpikeEventSeries or other source.
     is_a: NWBDataInterface
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       description:
         name: description
         description: Description of features (eg, ''PC1'') for each of the extracted
           features.
-        multivalued: false
-        range: FeatureExtraction__description
+        multivalued: true
+        range: text
         required: true
       features:
         name: features
@@ -103,8 +117,8 @@ classes:
       times:
         name: times
         description: Times of events that features correspond to (can be a link).
-        multivalued: false
-        range: FeatureExtraction__times
+        multivalued: true
+        range: float64
         required: true
       electrodes:
         name: electrodes
@@ -113,11 +127,16 @@ classes:
         multivalued: false
         range: FeatureExtraction__electrodes
         required: true
+    tree_root: true
   EventDetection:
     name: EventDetection
     description: Detected spike events from voltage trace(s).
     is_a: NWBDataInterface
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       detection_method:
         name: detection_method
         description: Description of how events were detected, such as voltage threshold,
@@ -131,15 +150,16 @@ classes:
           corresponding to time of event. ''description'' should define what is meant
           by time of event (e.g., .25 ms before action potential peak, zero-crossing
           time, etc). The index points to each event from the raw data.
-        multivalued: false
-        range: EventDetection__source_idx
+        multivalued: true
+        range: int32
         required: true
       times:
         name: times
         description: Timestamps of events, in seconds.
-        multivalued: false
-        range: EventDetection__times
+        multivalued: true
+        range: float64
         required: true
+    tree_root: true
   EventWaveform:
     name: EventWaveform
     description: Represents either the waveforms of detected events, as extracted
@@ -147,12 +167,17 @@ classes:
       during experiment acquisition.
     is_a: NWBDataInterface
     attributes:
-      SpikeEventSeries:
-        name: SpikeEventSeries
+      name:
+        name: name
+        range: string
+        required: true
+      spike_event_series:
+        name: spike_event_series
         description: SpikeEventSeries object(s) containing detected spike event waveforms.
         multivalued: true
         range: SpikeEventSeries
         required: false
+    tree_root: true
   FilteredEphys:
     name: FilteredEphys
     description: Electrophysiology data from one or more channels that has been subjected
@@ -168,13 +193,18 @@ classes:
       the ElectricalSeries 'filtering' attribute.
     is_a: NWBDataInterface
     attributes:
-      ElectricalSeries:
-        name: ElectricalSeries
+      name:
+        name: name
+        range: string
+        required: true
+      electrical_series:
+        name: electrical_series
         description: ElectricalSeries object(s) containing filtered electrophysiology
           data.
         multivalued: true
         range: ElectricalSeries
         required: true
+    tree_root: true
   LFP:
     name: LFP
     description: LFP data from one or more channels. The electrode map in each published
@@ -182,18 +212,27 @@ classes:
       properties should be noted in the ElectricalSeries 'filtering' attribute.
     is_a: NWBDataInterface
     attributes:
-      ElectricalSeries:
-        name: ElectricalSeries
+      name:
+        name: name
+        range: string
+        required: true
+      electrical_series:
+        name: electrical_series
         description: ElectricalSeries object(s) containing LFP data for one or more
           channels.
         multivalued: true
         range: ElectricalSeries
         required: true
+    tree_root: true
   ElectrodeGroup:
     name: ElectrodeGroup
     description: A physical grouping of electrodes, e.g. a shank of an array.
     is_a: NWBContainer
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       description:
         name: description
         description: Description of this electrode group.
@@ -210,6 +249,7 @@ classes:
         multivalued: false
         range: AnyType
         required: false
+    tree_root: true
   ClusterWaveforms:
     name: ClusterWaveforms
     description: DEPRECATED The mean waveform shape, including standard deviation,
@@ -220,6 +260,10 @@ classes:
       or an extension of this one.
     is_a: NWBDataInterface
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       waveform_filtering:
         name: waveform_filtering
         description: Filtering applied to data before generating mean/sd
@@ -242,12 +286,17 @@ classes:
         multivalued: false
         range: ClusterWaveforms__waveform_sd
         required: true
+    tree_root: true
   Clustering:
     name: Clustering
     description: DEPRECATED Clustered spike data, whether from automatic clustering
       tools (e.g., klustakwik) or as a result of manual sorting.
     is_a: NWBDataInterface
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       description:
         name: description
         description: Description of clusters or clustering, (e.g. cluster 0 is noise,
@@ -258,20 +307,21 @@ classes:
       num:
         name: num
         description: Cluster number of each event
-        multivalued: false
-        range: Clustering__num
+        multivalued: true
+        range: int32
         required: true
       peak_over_rms:
         name: peak_over_rms
         description: Maximum ratio of waveform peak to RMS on any channel in the cluster
           (provides a basic clustering metric).
-        multivalued: false
-        range: Clustering__peak_over_rms
+        multivalued: true
+        range: float32
         required: true
       times:
         name: times
         description: Times of clustered events, in seconds. This may be a link to
           times field in associated FeatureExtraction module.
-        multivalued: false
-        range: Clustering__times
+        multivalued: true
+        range: float64
         required: true
+    tree_root: true

nwb_linkml/schema/core.nwb.epoch.include.yaml

@@ -12,11 +12,32 @@ classes:
     name: TimeIntervals__tags_index
     description: Index for tags.
     is_a: VectorIndex
+    attributes:
+      name:
+        name: name
+        ifabsent: string(tags_index)
+        range: string
+        required: true
+        equals_string: tags_index
   TimeIntervals__timeseries:
     name: TimeIntervals__timeseries
     description: An index into a TimeSeries object.
     is_a: TimeSeriesReferenceVectorData
+    attributes:
+      name:
+        name: name
+        ifabsent: string(timeseries)
+        range: string
+        required: true
+        equals_string: timeseries
   TimeIntervals__timeseries_index:
     name: TimeIntervals__timeseries_index
     description: Index for timeseries.
     is_a: VectorIndex
+    attributes:
+      name:
+        name: name
+        ifabsent: string(timeseries_index)
+        range: string
+        required: true
+        equals_string: timeseries_index

nwb_linkml/schema/core.nwb.epoch.yaml

@@ -14,6 +14,10 @@ classes:
       epoch applies to.
     is_a: DynamicTable
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       start_time:
         name: start_time
         description: Start time of epoch, in seconds.
@@ -47,3 +51,4 @@ classes:
         multivalued: false
         range: TimeIntervals__timeseries_index
         required: false
+    tree_root: true

nwb_linkml/schema/core.nwb.file.include.yaml

@@ -15,116 +15,6 @@ imports:
 - core.nwb.file
 default_prefix: core.nwb.file.include/
 classes:
-  NWBFile__file_create_date:
-    name: NWBFile__file_create_date
-    description: 'A record of the date the file was created and of subsequent modifications.
-      The date is stored in UTC with local timezone offset as ISO 8601 extended formatted
-      strings: 2018-09-28T14:43:54.123+02:00. Dates stored in UTC end in "Z" with
-      no timezone offset. Date accuracy is up to milliseconds. The file can be created
-      after the experiment was run, so this may differ from the experiment start time.
-      Each modification to the nwb file adds a new entry to the array.'
-    attributes:
-      file_create_date:
-        name: file_create_date
-        description: 'A record of the date the file was created and of subsequent
-          modifications. The date is stored in UTC with local timezone offset as ISO
-          8601 extended formatted strings: 2018-09-28T14:43:54.123+02:00. Dates stored
-          in UTC end in "Z" with no timezone offset. Date accuracy is up to milliseconds.
-          The file can be created after the experiment was run, so this may differ
-          from the experiment start time. Each modification to the nwb file adds a
-          new entry to the array.'
-        multivalued: true
-        range: isodatetime
-        required: true
-  NWBFile__acquisition:
-    name: NWBFile__acquisition
-    description: Data streams recorded from the system, including ephys, ophys, tracking,
-      etc. This group should be read-only after the experiment is completed and timestamps
-      are corrected to a common timebase. The data stored here may be links to raw
-      data stored in external NWB files. This will allow keeping bulky raw data out
-      of the file while preserving the option of keeping some/all in the file. Acquired
-      data includes tracking and experimental data streams (i.e., everything measured
-      from the system). If bulky data is stored in the /acquisition group, the data
-      can exist in a separate NWB file that is linked to by the file being used for
-      processing and analysis.
-    attributes:
-      NWBDataInterface:
-        name: NWBDataInterface
-        description: Acquired, raw data.
-        multivalued: true
-        range: NWBDataInterface
-        required: false
-      DynamicTable:
-        name: DynamicTable
-        description: Tabular data that is relevant to acquisition
-        multivalued: true
-        range: DynamicTable
-        required: false
-  NWBFile__analysis:
-    name: NWBFile__analysis
-    description: Lab-specific and custom scientific analysis of data. There is no
-      defined format for the content of this group - the format is up to the individual
-      user/lab. To facilitate sharing analysis data between labs, the contents here
-      should be stored in standard types (e.g., neurodata_types) and appropriately
-      documented. The file can store lab-specific and custom data analysis without
-      restriction on its form or schema, reducing data formatting restrictions on
-      end users. Such data should be placed in the analysis group. The analysis data
-      should be documented so that it could be shared with other labs.
-    attributes:
-      NWBContainer:
-        name: NWBContainer
-        description: Custom analysis results.
-        multivalued: true
-        range: NWBContainer
-        required: false
-      DynamicTable:
-        name: DynamicTable
-        description: Tabular data that is relevant to data stored in analysis
-        multivalued: true
-        range: DynamicTable
-        required: false
-  NWBFile__scratch:
-    name: NWBFile__scratch
-    description: A place to store one-off analysis results. Data placed here is not
-      intended for sharing. By placing data here, users acknowledge that there is
-      no guarantee that their data meets any standard.
-    attributes:
-      ScratchData:
-        name: ScratchData
-        description: Any one-off datasets
-        multivalued: true
-        range: ScratchData
-        required: false
-      NWBContainer:
-        name: NWBContainer
-        description: Any one-off containers
-        multivalued: true
-        range: NWBContainer
-        required: false
-      DynamicTable:
-        name: DynamicTable
-        description: Any one-off tables
-        multivalued: true
-        range: DynamicTable
-        required: false
-  NWBFile__processing:
-    name: NWBFile__processing
-    description: The home for ProcessingModules. These modules perform intermediate
-      analysis of data that is necessary to perform before scientific analysis. Examples
-      include spike clustering, extracting position from tracking data, stitching
-      together image slices. ProcessingModules can be large and express many data
-      sets from relatively complex analysis (e.g., spike detection and clustering)
-      or small, representing extraction of position information from tracking video,
-      or even binary lick/no-lick decisions. Common software tools (e.g., klustakwik,
-      MClust) are expected to read/write data here.  'Processing' refers to intermediate
-      analysis of the acquired data to make it more amenable to scientific analysis.
-    attributes:
-      ProcessingModule:
-        name: ProcessingModule
-        description: Intermediate analysis of acquired data.
-        multivalued: true
-        range: ProcessingModule
-        required: false
   NWBFile__stimulus:
     name: NWBFile__stimulus
     description: Data pushed into the system (eg, video stimulus, sound, voltage,
@@ -140,50 +30,28 @@ classes:
       times. These templates can exist in the present file or can be linked to a remote
       library file.
     attributes:
+      name:
+        name: name
+        ifabsent: string(stimulus)
+        range: string
+        required: true
+        equals_string: stimulus
       presentation:
         name: presentation
         description: Stimuli presented during the experiment.
-        multivalued: false
-        range: NWBFile__stimulus__presentation
-        required: true
+        multivalued: true
+        any_of:
+        - range: TimeSeries
       templates:
         name: templates
         description: Template stimuli. Timestamps in templates are based on stimulus
           design and are relative to the beginning of the stimulus. When templates
           are used, the stimulus instances must convert presentation times to the
           experiment`s time reference frame.
-        multivalued: false
-        range: NWBFile__stimulus__templates
-        required: true
-  NWBFile__stimulus__presentation:
-    name: NWBFile__stimulus__presentation
-    description: Stimuli presented during the experiment.
-    attributes:
-      TimeSeries:
-        name: TimeSeries
-        description: TimeSeries objects containing data of presented stimuli.
         multivalued: true
-        range: TimeSeries
-        required: false
-  NWBFile__stimulus__templates:
-    name: NWBFile__stimulus__templates
-    description: Template stimuli. Timestamps in templates are based on stimulus design
-      and are relative to the beginning of the stimulus. When templates are used,
-      the stimulus instances must convert presentation times to the experiment`s time
-      reference frame.
-    attributes:
-      TimeSeries:
-        name: TimeSeries
-        description: TimeSeries objects containing template data of presented stimuli.
-        multivalued: true
-        range: TimeSeries
-        required: false
-      Images:
-        name: Images
-        description: Images objects containing images of presented stimuli.
-        multivalued: true
-        range: Images
-        required: false
+        any_of:
+        - range: TimeSeries
+        - range: Images
   NWBFile__general:
     name: NWBFile__general
     description: Experimental metadata, including protocol, notes and description
@@ -201,6 +69,12 @@ classes:
       when data is present. Unused groups (e.g., intracellular_ephys in an optophysiology
       experiment) should not be created unless there is data to store within them.
     attributes:
+      name:
+        name: name
+        ifabsent: string(general)
+        range: string
+        required: true
+        equals_string: general
       data_collection:
         name: data_collection
         description: Notes about data collection and analysis.
@@ -217,8 +91,8 @@ classes:
         name: experimenter
         description: Name of person(s) who performed the experiment. Can also specify
           roles of different people involved.
-        multivalued: false
-        range: NWBFile__general__experimenter
+        multivalued: true
+        range: text
         required: false
       institution:
         name: institution
@@ -229,8 +103,8 @@ classes:
       keywords:
         name: keywords
         description: Terms to search over.
-        multivalued: false
-        range: NWBFile__general__keywords
+        multivalued: true
+        range: text
         required: false
       lab:
         name: lab
@@ -261,8 +135,8 @@ classes:
       related_publications:
         name: related_publications
         description: Publication information. PMID, DOI, URL, etc.
-        multivalued: false
-        range: NWBFile__general__related_publications
+        multivalued: true
+        range: text
         required: false
       session_id:
         name: session_id
@@ -304,8 +178,8 @@ classes:
         multivalued: false
         range: text
         required: false
-      LabMetaData:
-        name: LabMetaData
+      lab_meta_data:
+        name: lab_meta_data
         description: Place-holder than can be extended so that lab-specific meta-data
           can be placed in /general.
         multivalued: true
@@ -315,15 +189,15 @@ classes:
         name: devices
         description: Description of hardware devices used during experiment, e.g.,
           monitors, ADC boards, microscopes, etc.
-        multivalued: false
-        range: NWBFile__general__devices
-        required: false
+        multivalued: true
+        any_of:
+        - range: Device
       subject:
         name: subject
         description: Information about the animal or person from which the data was
           measured.
         multivalued: false
-        range: NWBFile__general__subject
+        range: Subject
         required: false
       extracellular_ephys:
         name: extracellular_ephys
@@ -340,77 +214,42 @@ classes:
       optogenetics:
         name: optogenetics
         description: Metadata describing optogenetic stimuluation.
-        multivalued: false
-        range: NWBFile__general__optogenetics
-        required: false
+        multivalued: true
+        any_of:
+        - range: OptogeneticStimulusSite
       optophysiology:
         name: optophysiology
         description: Metadata related to optophysiology.
-        multivalued: false
-        range: NWBFile__general__optophysiology
-        required: false
-  NWBFile__general__experimenter:
-    name: NWBFile__general__experimenter
-    description: Name of person(s) who performed the experiment. Can also specify
-      roles of different people involved.
-    attributes:
-      experimenter:
-        name: experimenter
-        description: Name of person(s) who performed the experiment. Can also specify
-          roles of different people involved.
         multivalued: true
-        range: text
-        required: false
-  NWBFile__general__keywords:
-    name: NWBFile__general__keywords
-    description: Terms to search over.
-    attributes:
-      keywords:
-        name: keywords
-        description: Terms to search over.
-        multivalued: true
-        range: text
-        required: false
-  NWBFile__general__related_publications:
-    name: NWBFile__general__related_publications
-    description: Publication information. PMID, DOI, URL, etc.
-    attributes:
-      related_publications:
-        name: related_publications
-        description: Publication information. PMID, DOI, URL, etc.
-        multivalued: true
-        range: text
-        required: false
+        any_of:
+        - range: ImagingPlane
   NWBFile__general__source_script:
     name: NWBFile__general__source_script
     description: Script file or link to public source code used to create this NWB
       file.
     attributes:
+      name:
+        name: name
+        ifabsent: string(source_script)
+        range: string
+        required: true
+        equals_string: source_script
       file_name:
         name: file_name
         description: Name of script file.
         range: text
-  NWBFile__general__devices:
-    name: NWBFile__general__devices
-    description: Description of hardware devices used during experiment, e.g., monitors,
-      ADC boards, microscopes, etc.
-    attributes:
-      Device:
-        name: Device
-        description: Data acquisition devices.
-        multivalued: true
-        range: Device
-        required: false
-  NWBFile__general__subject:
-    name: NWBFile__general__subject
-    description: Information about the animal or person from which the data was measured.
-    is_a: Subject
   NWBFile__general__extracellular_ephys:
     name: NWBFile__general__extracellular_ephys
     description: Metadata related to extracellular electrophysiology.
     attributes:
-      ElectrodeGroup:
-        name: ElectrodeGroup
+      name:
+        name: name
+        ifabsent: string(extracellular_ephys)
+        range: string
+        required: true
+        equals_string: extracellular_ephys
+      electrode_group:
+        name: electrode_group
         description: Physical group of electrodes.
         multivalued: true
         range: ElectrodeGroup
@@ -419,82 +258,18 @@ classes:
         name: electrodes
         description: A table of all electrodes (i.e. channels) used for recording.
         multivalued: false
-        range: NWBFile__general__extracellular_ephys__electrodes
+        range: DynamicTable
         required: false
-  NWBFile__general__extracellular_ephys__electrodes:
-    name: NWBFile__general__extracellular_ephys__electrodes
-    description: A table of all electrodes (i.e. channels) used for recording.
-    is_a: DynamicTable
-    attributes:
-      x:
-        name: x
-        description: x coordinate of the channel location in the brain (+x is posterior).
-        multivalued: true
-        range: float32
-      y:
-        name: y
-        description: y coordinate of the channel location in the brain (+y is inferior).
-        multivalued: true
-        range: float32
-      z:
-        name: z
-        description: z coordinate of the channel location in the brain (+z is right).
-        multivalued: true
-        range: float32
-      imp:
-        name: imp
-        description: Impedance of the channel, in ohms.
-        multivalued: true
-        range: float32
-      location:
-        name: location
-        description: Location of the electrode (channel). Specify the area, layer,
-          comments on estimation of area/layer, stereotaxic coordinates if in vivo,
-          etc. Use standard atlas names for anatomical regions when possible.
-        multivalued: true
-        range: text
-      filtering:
-        name: filtering
-        description: Description of hardware filtering, including the filter name
-          and frequency cutoffs.
-        multivalued: true
-        range: text
-      group:
-        name: group
-        description: Reference to the ElectrodeGroup this electrode is a part of.
-        multivalued: true
-        range: ElectrodeGroup
-      group_name:
-        name: group_name
-        description: Name of the ElectrodeGroup this electrode is a part of.
-        multivalued: true
-        range: text
-      rel_x:
-        name: rel_x
-        description: x coordinate in electrode group
-        multivalued: true
-        range: float32
-      rel_y:
-        name: rel_y
-        description: y coordinate in electrode group
-        multivalued: true
-        range: float32
-      rel_z:
-        name: rel_z
-        description: z coordinate in electrode group
-        multivalued: true
-        range: float32
-      reference:
-        name: reference
-        description: Description of the reference electrode and/or reference scheme
-          used for this electrode, e.g., "stainless steel skull screw" or "online
-          common average referencing".
-        multivalued: true
-        range: text
   NWBFile__general__intracellular_ephys:
     name: NWBFile__general__intracellular_ephys
     description: Metadata related to intracellular electrophysiology.
     attributes:
+      name:
+        name: name
+        ifabsent: string(intracellular_ephys)
+        range: string
+        required: true
+        equals_string: intracellular_ephys
       filtering:
         name: filtering
         description: '[DEPRECATED] Use IntracellularElectrode.filtering instead. Description
@@ -504,8 +279,8 @@ classes:
         multivalued: false
         range: text
         required: false
-      IntracellularElectrode:
-        name: IntracellularElectrode
+      intracellular_electrode:
+        name: intracellular_electrode
         description: An intracellular electrode.
         multivalued: true
         range: IntracellularElectrode
@@ -517,7 +292,7 @@ classes:
           tables. Additional SequentialRecordingsTable, RepetitionsTable and ExperimentalConditions
           tables provide enhanced support for experiment metadata.'
         multivalued: false
-        range: NWBFile__general__intracellular_ephys__sweep_table
+        range: SweepTable
         required: false
       intracellular_recordings:
         name: intracellular_recordings
@@ -534,7 +309,7 @@ classes:
           to an electrode is also common in intracellular electrophysiology, in which
           case other TimeSeries may be used.
         multivalued: false
-        range: NWBFile__general__intracellular_ephys__intracellular_recordings
+        range: IntracellularRecordingsTable
         required: false
       simultaneous_recordings:
         name: simultaneous_recordings
@@ -542,7 +317,7 @@ classes:
           the IntracellularRecordingsTable table together that were recorded simultaneously
           from different electrodes
         multivalued: false
-        range: NWBFile__general__intracellular_ephys__simultaneous_recordings
+        range: SimultaneousRecordingsTable
         required: false
       sequential_recordings:
         name: sequential_recordings
@@ -551,7 +326,7 @@ classes:
           together sequential recordings where the a sequence of stimuli of the same
           type with varying parameters have been presented in a sequence.
         multivalued: false
-        range: NWBFile__general__intracellular_ephys__sequential_recordings
+        range: SequentialRecordingsTable
         required: false
       repetitions:
         name: repetitions
@@ -560,80 +335,14 @@ classes:
           type of stimulus, the RepetitionsTable table is typically used to group
           sets of stimuli applied in sequence.
         multivalued: false
-        range: NWBFile__general__intracellular_ephys__repetitions
+        range: RepetitionsTable
         required: false
       experimental_conditions:
         name: experimental_conditions
         description: A table for grouping different intracellular recording repetitions
           together that belong to the same experimental experimental_conditions.
         multivalued: false
-        range: NWBFile__general__intracellular_ephys__experimental_conditions
-        required: false
-  NWBFile__general__intracellular_ephys__sweep_table:
-    name: NWBFile__general__intracellular_ephys__sweep_table
-    description: '[DEPRECATED] Table used to group different PatchClampSeries. SweepTable
-      is being replaced by IntracellularRecordingsTable and SimultaneousRecordingsTable
-      tables. Additional SequentialRecordingsTable, RepetitionsTable and ExperimentalConditions
-      tables provide enhanced support for experiment metadata.'
-    is_a: SweepTable
-  NWBFile__general__intracellular_ephys__intracellular_recordings:
-    name: NWBFile__general__intracellular_ephys__intracellular_recordings
-    description: A table to group together a stimulus and response from a single electrode
-      and a single simultaneous recording. Each row in the table represents a single
-      recording consisting typically of a stimulus and a corresponding response. In
-      some cases, however, only a stimulus or a response are recorded as as part of
-      an experiment. In this case both, the stimulus and response will point to the
-      same TimeSeries while the idx_start and count of the invalid column will be
-      set to -1, thus, indicating that no values have been recorded for the stimulus
-      or response, respectively. Note, a recording MUST contain at least a stimulus
-      or a response. Typically the stimulus and response are PatchClampSeries. However,
-      the use of AD/DA channels that are not associated to an electrode is also common
-      in intracellular electrophysiology, in which case other TimeSeries may be used.
-    is_a: IntracellularRecordingsTable
-  NWBFile__general__intracellular_ephys__simultaneous_recordings:
-    name: NWBFile__general__intracellular_ephys__simultaneous_recordings
-    description: A table for grouping different intracellular recordings from the
-      IntracellularRecordingsTable table together that were recorded simultaneously
-      from different electrodes
-    is_a: SimultaneousRecordingsTable
-  NWBFile__general__intracellular_ephys__sequential_recordings:
-    name: NWBFile__general__intracellular_ephys__sequential_recordings
-    description: A table for grouping different sequential recordings from the SimultaneousRecordingsTable
-      table together. This is typically used to group together sequential recordings
-      where the a sequence of stimuli of the same type with varying parameters have
-      been presented in a sequence.
-    is_a: SequentialRecordingsTable
-  NWBFile__general__intracellular_ephys__repetitions:
-    name: NWBFile__general__intracellular_ephys__repetitions
-    description: A table for grouping different sequential intracellular recordings
-      together. With each SequentialRecording typically representing a particular
-      type of stimulus, the RepetitionsTable table is typically used to group sets
-      of stimuli applied in sequence.
-    is_a: RepetitionsTable
-  NWBFile__general__intracellular_ephys__experimental_conditions:
-    name: NWBFile__general__intracellular_ephys__experimental_conditions
-    description: A table for grouping different intracellular recording repetitions
-      together that belong to the same experimental experimental_conditions.
-    is_a: ExperimentalConditionsTable
-  NWBFile__general__optogenetics:
-    name: NWBFile__general__optogenetics
-    description: Metadata describing optogenetic stimuluation.
-    attributes:
-      OptogeneticStimulusSite:
-        name: OptogeneticStimulusSite
-        description: An optogenetic stimulation site.
-        multivalued: true
-        range: OptogeneticStimulusSite
-        required: false
-  NWBFile__general__optophysiology:
-    name: NWBFile__general__optophysiology
-    description: Metadata related to optophysiology.
-    attributes:
-      ImagingPlane:
-        name: ImagingPlane
-        description: An imaging plane.
-        multivalued: true
-        range: ImagingPlane
+        range: ExperimentalConditionsTable
         required: false
   NWBFile__intervals:
     name: NWBFile__intervals
@@ -641,53 +350,48 @@ classes:
       having a particular scientific goal, trials (see trials subgroup) during an
       experiment, or epochs (see epochs subgroup) deriving from analysis of data.
     attributes:
+      name:
+        name: name
+        ifabsent: string(intervals)
+        range: string
+        required: true
+        equals_string: intervals
       epochs:
         name: epochs
         description: Divisions in time marking experimental stages or sub-divisions
           of a single recording session.
         multivalued: false
-        range: NWBFile__intervals__epochs
+        range: TimeIntervals
         required: false
       trials:
         name: trials
         description: Repeated experimental events that have a logical grouping.
         multivalued: false
-        range: NWBFile__intervals__trials
+        range: TimeIntervals
         required: false
       invalid_times:
         name: invalid_times
         description: Time intervals that should be removed from analysis.
         multivalued: false
-        range: NWBFile__intervals__invalid_times
+        range: TimeIntervals
         required: false
-      TimeIntervals:
-        name: TimeIntervals
+      time_intervals:
+        name: time_intervals
         description: Optional additional table(s) for describing other experimental
           time intervals.
         multivalued: true
         range: TimeIntervals
         required: false
-  NWBFile__intervals__epochs:
-    name: NWBFile__intervals__epochs
-    description: Divisions in time marking experimental stages or sub-divisions of
-      a single recording session.
-    is_a: TimeIntervals
-  NWBFile__intervals__trials:
-    name: NWBFile__intervals__trials
-    description: Repeated experimental events that have a logical grouping.
-    is_a: TimeIntervals
-  NWBFile__intervals__invalid_times:
-    name: NWBFile__intervals__invalid_times
-    description: Time intervals that should be removed from analysis.
-    is_a: TimeIntervals
-  NWBFile__units:
-    name: NWBFile__units
-    description: Data about sorted spike units.
-    is_a: Units
   Subject__age:
     name: Subject__age
     description: Age of subject. Can be supplied instead of 'date_of_birth'.
     attributes:
+      name:
+        name: name
+        ifabsent: string(age)
+        range: string
+        required: true
+        equals_string: age
       reference:
         name: reference
         description: Age is with reference to this event. Can be 'birth' or 'gestational'.

nwb_linkml/schema/core.nwb.file.yaml

@@ -20,16 +20,27 @@ classes:
     description: Any one-off datasets
     is_a: NWBData
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       notes:
         name: notes
         description: Any notes the user has about the dataset being stored
         range: text
+    tree_root: true
   NWBFile:
     name: NWBFile
     description: An NWB file storing cellular-based neurophysiology data from a single
       experimental session.
     is_a: NWBContainer
     attributes:
+      name:
+        name: name
+        ifabsent: string(root)
+        range: string
+        required: true
+        equals_string: root
       nwb_version:
         name: nwb_version
         description: File version string. Use semantic versioning, e.g. 1.2.1. This
@@ -44,8 +55,8 @@ classes:
           The file can be created after the experiment was run, so this may differ
           from the experiment start time. Each modification to the nwb file adds a
           new entry to the array.'
-        multivalued: false
-        range: NWBFile__file_create_date
+        multivalued: true
+        range: isodatetime
         required: true
       identifier:
         name: identifier
@@ -92,9 +103,10 @@ classes:
           (i.e., everything measured from the system). If bulky data is stored in
           the /acquisition group, the data can exist in a separate NWB file that is
           linked to by the file being used for processing and analysis.
-        multivalued: false
-        range: NWBFile__acquisition
-        required: true
+        multivalued: true
+        any_of:
+        - range: NWBDataInterface
+        - range: DynamicTable
       analysis:
         name: analysis
         description: Lab-specific and custom scientific analysis of data. There is
@@ -106,17 +118,19 @@ classes:
           restrictions on end users. Such data should be placed in the analysis group.
           The analysis data should be documented so that it could be shared with other
           labs.
-        multivalued: false
-        range: NWBFile__analysis
-        required: true
+        multivalued: true
+        any_of:
+        - range: NWBContainer
+        - range: DynamicTable
       scratch:
         name: scratch
         description: A place to store one-off analysis results. Data placed here is
           not intended for sharing. By placing data here, users acknowledge that there
           is no guarantee that their data meets any standard.
-        multivalued: false
-        range: NWBFile__scratch
-        required: false
+        multivalued: true
+        any_of:
+        - range: NWBContainer
+        - range: DynamicTable
       processing:
         name: processing
         description: The home for ProcessingModules. These modules perform intermediate
@@ -129,9 +143,9 @@ classes:
           (e.g., klustakwik, MClust) are expected to read/write data here.  'Processing'
           refers to intermediate analysis of the acquired data to make it more amenable
           to scientific analysis.
-        multivalued: false
-        range: NWBFile__processing
-        required: true
+        multivalued: true
+        any_of:
+        - range: ProcessingModule
       stimulus:
         name: stimulus
         description: Data pushed into the system (eg, video stimulus, sound, voltage,
@@ -182,17 +196,28 @@ classes:
         name: units
         description: Data about sorted spike units.
         multivalued: false
-        range: NWBFile__units
+        range: Units
         required: false
+    tree_root: true
   LabMetaData:
     name: LabMetaData
     description: Lab-specific meta-data.
     is_a: NWBContainer
+    attributes:
+      name:
+        name: name
+        range: string
+        required: true
+    tree_root: true
   Subject:
     name: Subject
     description: Information about the animal or person from which the data was measured.
     is_a: NWBContainer
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       age:
         name: age
         description: Age of subject. Can be supplied instead of 'date_of_birth'.
@@ -249,3 +274,4 @@ classes:
         multivalued: false
         range: text
         required: false
+    tree_root: true

nwb_linkml/schema/core.nwb.icephys.include.yaml

@@ -9,26 +9,16 @@ imports:
 - core.nwb.icephys
 default_prefix: core.nwb.icephys.include/
 classes:
-  PatchClampSeries__data:
-    name: PatchClampSeries__data
-    description: Recorded voltage or current.
-    attributes:
-      unit:
-        name: unit
-        description: Base unit of measurement for working with the data. Actual stored
-          values are not necessarily stored in these units. To access the data in
-          these units, multiply 'data' by 'conversion' and add 'offset'.
-        range: text
-      data:
-        name: data
-        description: Recorded voltage or current.
-        multivalued: true
-        range: numeric
-        required: true
   CurrentClampSeries__data:
     name: CurrentClampSeries__data
     description: Recorded voltage.
     attributes:
+      name:
+        name: name
+        ifabsent: string(data)
+        range: string
+        required: true
+        equals_string: data
       unit:
         name: unit
         description: Base unit of measurement for working with the data. which is
@@ -40,6 +30,12 @@ classes:
     name: CurrentClampStimulusSeries__data
     description: Stimulus current applied.
     attributes:
+      name:
+        name: name
+        ifabsent: string(data)
+        range: string
+        required: true
+        equals_string: data
       unit:
         name: unit
         description: Base unit of measurement for working with the data. which is
@@ -51,6 +47,12 @@ classes:
     name: VoltageClampSeries__data
     description: Recorded current.
     attributes:
+      name:
+        name: name
+        ifabsent: string(data)
+        range: string
+        required: true
+        equals_string: data
       unit:
         name: unit
         description: Base unit of measurement for working with the data. which is
@@ -62,6 +64,12 @@ classes:
     name: VoltageClampSeries__capacitance_fast
     description: Fast capacitance, in farads.
     attributes:
+      name:
+        name: name
+        ifabsent: string(capacitance_fast)
+        range: string
+        required: true
+        equals_string: capacitance_fast
       unit:
         name: unit
         description: Unit of measurement for capacitance_fast, which is fixed to 'farads'.
@@ -70,6 +78,12 @@ classes:
     name: VoltageClampSeries__capacitance_slow
     description: Slow capacitance, in farads.
     attributes:
+      name:
+        name: name
+        ifabsent: string(capacitance_slow)
+        range: string
+        required: true
+        equals_string: capacitance_slow
       unit:
         name: unit
         description: Unit of measurement for capacitance_fast, which is fixed to 'farads'.
@@ -78,6 +92,12 @@ classes:
     name: VoltageClampSeries__resistance_comp_bandwidth
     description: Resistance compensation bandwidth, in hertz.
     attributes:
+      name:
+        name: name
+        ifabsent: string(resistance_comp_bandwidth)
+        range: string
+        required: true
+        equals_string: resistance_comp_bandwidth
       unit:
         name: unit
         description: Unit of measurement for resistance_comp_bandwidth, which is fixed
@@ -87,6 +107,12 @@ classes:
     name: VoltageClampSeries__resistance_comp_correction
     description: Resistance compensation correction, in percent.
     attributes:
+      name:
+        name: name
+        ifabsent: string(resistance_comp_correction)
+        range: string
+        required: true
+        equals_string: resistance_comp_correction
       unit:
         name: unit
         description: Unit of measurement for resistance_comp_correction, which is
@@ -96,6 +122,12 @@ classes:
     name: VoltageClampSeries__resistance_comp_prediction
     description: Resistance compensation prediction, in percent.
     attributes:
+      name:
+        name: name
+        ifabsent: string(resistance_comp_prediction)
+        range: string
+        required: true
+        equals_string: resistance_comp_prediction
       unit:
         name: unit
         description: Unit of measurement for resistance_comp_prediction, which is
@@ -105,6 +137,12 @@ classes:
     name: VoltageClampSeries__whole_cell_capacitance_comp
     description: Whole cell capacitance compensation, in farads.
     attributes:
+      name:
+        name: name
+        ifabsent: string(whole_cell_capacitance_comp)
+        range: string
+        required: true
+        equals_string: whole_cell_capacitance_comp
       unit:
         name: unit
         description: Unit of measurement for whole_cell_capacitance_comp, which is
@@ -114,6 +152,12 @@ classes:
     name: VoltageClampSeries__whole_cell_series_resistance_comp
     description: Whole cell series resistance compensation, in ohms.
     attributes:
+      name:
+        name: name
+        ifabsent: string(whole_cell_series_resistance_comp)
+        range: string
+        required: true
+        equals_string: whole_cell_series_resistance_comp
       unit:
         name: unit
         description: Unit of measurement for whole_cell_series_resistance_comp, which
@@ -123,6 +167,12 @@ classes:
     name: VoltageClampStimulusSeries__data
     description: Stimulus voltage applied.
     attributes:
+      name:
+        name: name
+        ifabsent: string(data)
+        range: string
+        required: true
+        equals_string: data
       unit:
         name: unit
         description: Base unit of measurement for working with the data. which is
@@ -134,34 +184,49 @@ classes:
     name: SweepTable__series_index
     description: Index for series.
     is_a: VectorIndex
+    attributes:
+      name:
+        name: name
+        ifabsent: string(series_index)
+        range: string
+        required: true
+        equals_string: series_index
   IntracellularStimuliTable__stimulus:
     name: IntracellularStimuliTable__stimulus
     description: Column storing the reference to the recorded stimulus for the recording
       (rows).
     is_a: TimeSeriesReferenceVectorData
+    attributes:
+      name:
+        name: name
+        ifabsent: string(stimulus)
+        range: string
+        required: true
+        equals_string: stimulus
   IntracellularResponsesTable__response:
     name: IntracellularResponsesTable__response
     description: Column storing the reference to the recorded response for the recording
       (rows)
     is_a: TimeSeriesReferenceVectorData
-  IntracellularRecordingsTable__electrodes:
-    name: IntracellularRecordingsTable__electrodes
-    description: Table for storing intracellular electrode related metadata.
-    is_a: IntracellularElectrodesTable
-  IntracellularRecordingsTable__stimuli:
-    name: IntracellularRecordingsTable__stimuli
-    description: Table for storing intracellular stimulus related metadata.
-    is_a: IntracellularStimuliTable
-  IntracellularRecordingsTable__responses:
-    name: IntracellularRecordingsTable__responses
-    description: Table for storing intracellular response related metadata.
-    is_a: IntracellularResponsesTable
+    attributes:
+      name:
+        name: name
+        ifabsent: string(response)
+        range: string
+        required: true
+        equals_string: response
   SimultaneousRecordingsTable__recordings:
     name: SimultaneousRecordingsTable__recordings
     description: A reference to one or more rows in the IntracellularRecordingsTable
       table.
     is_a: DynamicTableRegion
     attributes:
+      name:
+        name: name
+        ifabsent: string(recordings)
+        range: string
+        required: true
+        equals_string: recordings
       table:
         name: table
         description: Reference to the IntracellularRecordingsTable table that this
@@ -172,12 +237,25 @@ classes:
     name: SimultaneousRecordingsTable__recordings_index
     description: Index dataset for the recordings column.
     is_a: VectorIndex
+    attributes:
+      name:
+        name: name
+        ifabsent: string(recordings_index)
+        range: string
+        required: true
+        equals_string: recordings_index
   SequentialRecordingsTable__simultaneous_recordings:
     name: SequentialRecordingsTable__simultaneous_recordings
     description: A reference to one or more rows in the SimultaneousRecordingsTable
       table.
     is_a: DynamicTableRegion
     attributes:
+      name:
+        name: name
+        ifabsent: string(simultaneous_recordings)
+        range: string
+        required: true
+        equals_string: simultaneous_recordings
       table:
         name: table
         description: Reference to the SimultaneousRecordingsTable table that this
@@ -188,12 +266,25 @@ classes:
     name: SequentialRecordingsTable__simultaneous_recordings_index
     description: Index dataset for the simultaneous_recordings column.
     is_a: VectorIndex
+    attributes:
+      name:
+        name: name
+        ifabsent: string(simultaneous_recordings_index)
+        range: string
+        required: true
+        equals_string: simultaneous_recordings_index
   RepetitionsTable__sequential_recordings:
     name: RepetitionsTable__sequential_recordings
     description: A reference to one or more rows in the SequentialRecordingsTable
       table.
     is_a: DynamicTableRegion
     attributes:
+      name:
+        name: name
+        ifabsent: string(sequential_recordings)
+        range: string
+        required: true
+        equals_string: sequential_recordings
       table:
         name: table
         description: Reference to the SequentialRecordingsTable table that this table
@@ -204,11 +295,24 @@ classes:
     name: RepetitionsTable__sequential_recordings_index
     description: Index dataset for the sequential_recordings column.
     is_a: VectorIndex
+    attributes:
+      name:
+        name: name
+        ifabsent: string(sequential_recordings_index)
+        range: string
+        required: true
+        equals_string: sequential_recordings_index
   ExperimentalConditionsTable__repetitions:
     name: ExperimentalConditionsTable__repetitions
     description: A reference to one or more rows in the RepetitionsTable table.
     is_a: DynamicTableRegion
     attributes:
+      name:
+        name: name
+        ifabsent: string(repetitions)
+        range: string
+        required: true
+        equals_string: repetitions
       table:
         name: table
         description: Reference to the RepetitionsTable table that this table region
@@ -219,3 +323,10 @@ classes:
     name: ExperimentalConditionsTable__repetitions_index
     description: Index dataset for the repetitions column.
     is_a: VectorIndex
+    attributes:
+      name:
+        name: name
+        ifabsent: string(repetitions_index)
+        range: string
+        required: true
+        equals_string: repetitions_index

nwb_linkml/schema/core.nwb.icephys.yaml

@@ -15,6 +15,10 @@ classes:
       current or voltage.
     is_a: TimeSeries
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       stimulus_description:
         name: stimulus_description
         description: Protocol/stimulus name for this patch-clamp dataset.
@@ -26,8 +30,8 @@ classes:
       data:
         name: data
         description: Recorded voltage or current.
-        multivalued: false
-        range: PatchClampSeries__data
+        multivalued: true
+        range: numeric
         required: true
       gain:
         name: gain
@@ -36,6 +40,7 @@ classes:
         multivalued: false
         range: float32
         required: false
+    tree_root: true
   CurrentClampSeries:
     name: CurrentClampSeries
     description: Voltage data from an intracellular current-clamp recording. A corresponding
@@ -43,6 +48,10 @@ classes:
       the current injected.
     is_a: PatchClampSeries
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       data:
         name: data
         description: Recorded voltage.
@@ -67,6 +76,7 @@ classes:
         multivalued: false
         range: float32
         required: false
+    tree_root: true
   IZeroClampSeries:
     name: IZeroClampSeries
     description: Voltage data from an intracellular recording when all current and
@@ -75,6 +85,10 @@ classes:
       amplifier is disconnected and no stimulus can reach the cell.
     is_a: CurrentClampSeries
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       stimulus_description:
         name: stimulus_description
         description: An IZeroClampSeries has no stimulus, so this attribute is automatically
@@ -98,17 +112,23 @@ classes:
         multivalued: false
         range: float32
         required: true
+    tree_root: true
   CurrentClampStimulusSeries:
     name: CurrentClampStimulusSeries
     description: Stimulus current applied during current clamp recording.
     is_a: PatchClampSeries
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       data:
         name: data
         description: Stimulus current applied.
         multivalued: false
         range: CurrentClampStimulusSeries__data
         required: true
+    tree_root: true
   VoltageClampSeries:
     name: VoltageClampSeries
     description: Current data from an intracellular voltage-clamp recording. A corresponding
@@ -116,6 +136,10 @@ classes:
       the voltage injected.
     is_a: PatchClampSeries
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       data:
         name: data
         description: Recorded current.
@@ -164,22 +188,32 @@ classes:
         multivalued: false
         range: VoltageClampSeries__whole_cell_series_resistance_comp
         required: false
+    tree_root: true
   VoltageClampStimulusSeries:
     name: VoltageClampStimulusSeries
     description: Stimulus voltage applied during a voltage clamp recording.
     is_a: PatchClampSeries
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       data:
         name: data
         description: Stimulus voltage applied.
         multivalued: false
         range: VoltageClampStimulusSeries__data
         required: true
+    tree_root: true
   IntracellularElectrode:
     name: IntracellularElectrode
     description: An intracellular electrode and its metadata.
     is_a: NWBContainer
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       cell_id:
         name: cell_id
         description: unique ID of the cell
@@ -230,6 +264,7 @@ classes:
         multivalued: false
         range: text
         required: false
+    tree_root: true
   SweepTable:
     name: SweepTable
     description: '[DEPRECATED] Table used to group different PatchClampSeries. SweepTable
@@ -238,6 +273,10 @@ classes:
       tables provide enhanced support for experiment metadata.'
     is_a: DynamicTable
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       sweep_number:
         name: sweep_number
         description: Sweep number of the PatchClampSeries in that row.
@@ -254,11 +293,16 @@ classes:
         multivalued: false
         range: SweepTable__series_index
         required: true
+    tree_root: true
   IntracellularElectrodesTable:
     name: IntracellularElectrodesTable
     description: Table for storing intracellular electrode related metadata.
     is_a: DynamicTable
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       description:
         name: description
         description: Description of what is in this dynamic table.
@@ -268,11 +312,16 @@ classes:
         description: Column for storing the reference to the intracellular electrode.
         multivalued: true
         range: IntracellularElectrode
+    tree_root: true
   IntracellularStimuliTable:
     name: IntracellularStimuliTable
     description: Table for storing intracellular stimulus related metadata.
     is_a: DynamicTable
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       description:
         name: description
         description: Description of what is in this dynamic table.
@@ -284,11 +333,16 @@ classes:
         multivalued: false
         range: IntracellularStimuliTable__stimulus
         required: true
+    tree_root: true
   IntracellularResponsesTable:
     name: IntracellularResponsesTable
     description: Table for storing intracellular response related metadata.
     is_a: DynamicTable
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       description:
         name: description
         description: Description of what is in this dynamic table.
@@ -300,6 +354,7 @@ classes:
         multivalued: false
         range: IntracellularResponsesTable__response
         required: true
+    tree_root: true
   IntracellularRecordingsTable:
     name: IntracellularRecordingsTable
     description: A table to group together a stimulus and response from a single electrode
@@ -315,6 +370,12 @@ classes:
       electrophysiology, in which case other TimeSeries may be used.
     is_a: AlignedDynamicTable
     attributes:
+      name:
+        name: name
+        ifabsent: string(intracellular_recordings)
+        range: string
+        required: true
+        equals_string: intracellular_recordings
       description:
         name: description
         description: Description of the contents of this table. Inherited from AlignedDynamicTable
@@ -324,20 +385,21 @@ classes:
         name: electrodes
         description: Table for storing intracellular electrode related metadata.
         multivalued: false
-        range: IntracellularRecordingsTable__electrodes
+        range: IntracellularElectrodesTable
         required: true
       stimuli:
         name: stimuli
         description: Table for storing intracellular stimulus related metadata.
         multivalued: false
-        range: IntracellularRecordingsTable__stimuli
+        range: IntracellularStimuliTable
         required: true
       responses:
         name: responses
         description: Table for storing intracellular response related metadata.
         multivalued: false
-        range: IntracellularRecordingsTable__responses
+        range: IntracellularResponsesTable
         required: true
+    tree_root: true
   SimultaneousRecordingsTable:
     name: SimultaneousRecordingsTable
     description: A table for grouping different intracellular recordings from the
@@ -345,6 +407,12 @@ classes:
       from different electrodes.
     is_a: DynamicTable
     attributes:
+      name:
+        name: name
+        ifabsent: string(simultaneous_recordings)
+        range: string
+        required: true
+        equals_string: simultaneous_recordings
       recordings:
         name: recordings
         description: A reference to one or more rows in the IntracellularRecordingsTable
@@ -358,6 +426,7 @@ classes:
         multivalued: false
         range: SimultaneousRecordingsTable__recordings_index
         required: true
+    tree_root: true
   SequentialRecordingsTable:
     name: SequentialRecordingsTable
     description: A table for grouping different sequential recordings from the SimultaneousRecordingsTable
@@ -366,6 +435,12 @@ classes:
       presented in a sequence.
     is_a: DynamicTable
     attributes:
+      name:
+        name: name
+        ifabsent: string(sequential_recordings)
+        range: string
+        required: true
+        equals_string: sequential_recordings
       simultaneous_recordings:
         name: simultaneous_recordings
         description: A reference to one or more rows in the SimultaneousRecordingsTable
@@ -384,6 +459,7 @@ classes:
         description: The type of stimulus used for the sequential recording.
         multivalued: true
         range: text
+    tree_root: true
   RepetitionsTable:
     name: RepetitionsTable
     description: A table for grouping different sequential intracellular recordings
@@ -392,6 +468,12 @@ classes:
       of stimuli applied in sequence.
     is_a: DynamicTable
     attributes:
+      name:
+        name: name
+        ifabsent: string(repetitions)
+        range: string
+        required: true
+        equals_string: repetitions
       sequential_recordings:
         name: sequential_recordings
         description: A reference to one or more rows in the SequentialRecordingsTable
@@ -405,12 +487,19 @@ classes:
         multivalued: false
         range: RepetitionsTable__sequential_recordings_index
         required: true
+    tree_root: true
   ExperimentalConditionsTable:
     name: ExperimentalConditionsTable
     description: A table for grouping different intracellular recording repetitions
       together that belong to the same experimental condition.
     is_a: DynamicTable
     attributes:
+      name:
+        name: name
+        ifabsent: string(experimental_conditions)
+        range: string
+        required: true
+        equals_string: experimental_conditions
       repetitions:
         name: repetitions
         description: A reference to one or more rows in the RepetitionsTable table.
@@ -423,3 +512,4 @@ classes:
         multivalued: false
         range: ExperimentalConditionsTable__repetitions_index
         required: true
+    tree_root: true

nwb_linkml/schema/core.nwb.image.include.yaml

@@ -15,11 +15,11 @@ classes:
       x:
         name: x
         range: numeric
-        required: false
+        required: true
       y:
         name: y
         range: numeric
-        required: false
+        required: true
   RGBImage__Array:
     name: RGBImage__Array
     is_a: Arraylike
@@ -27,15 +27,15 @@ classes:
       x:
         name: x
         range: numeric
-        required: false
+        required: true
       y:
         name: y
         range: numeric
-        required: false
+        required: true
       r, g, b:
         name: r, g, b
         range: numeric
-        required: false
+        required: true
         minimum_cardinality: 3
         maximum_cardinality: 3
   RGBAImage__Array:
@@ -45,15 +45,15 @@ classes:
       x:
         name: x
         range: numeric
-        required: false
+        required: true
       y:
         name: y
         range: numeric
-        required: false
+        required: true
       r, g, b, a:
         name: r, g, b, a
         range: numeric
-        required: false
+        required: true
         minimum_cardinality: 4
         maximum_cardinality: 4
   ImageSeries__data:
@@ -61,6 +61,12 @@ classes:
     description: Binary data representing images across frames. If data are stored
       in an external file, this should be an empty 3D array.
     attributes:
+      name:
+        name: name
+        ifabsent: string(data)
+        range: string
+        required: true
+        equals_string: data
       array:
         name: array
         range: ImageSeries__data__Array
@@ -84,52 +90,16 @@ classes:
         name: z
         range: numeric
         required: false
-  ImageSeries__dimension:
-    name: ImageSeries__dimension
-    description: Number of pixels on x, y, (and z) axes.
-    attributes:
-      dimension:
-        name: dimension
-        description: Number of pixels on x, y, (and z) axes.
-        multivalued: true
-        range: int32
-        required: false
-  ImageSeries__external_file:
-    name: ImageSeries__external_file
-    description: Paths to one or more external file(s). The field is only present
-      if format='external'. This is only relevant if the image series is stored in
-      the file system as one or more image file(s). This field should NOT be used
-      if the image is stored in another NWB file and that file is linked to this file.
-    attributes:
-      starting_frame:
-        name: starting_frame
-        description: Each external image may contain one or more consecutive frames
-          of the full ImageSeries. This attribute serves as an index to indicate which
-          frames each file contains, to facilitate random access. The 'starting_frame'
-          attribute, hence, contains a list of frame numbers within the full ImageSeries
-          of the first frame of each file listed in the parent 'external_file' dataset.
-          Zero-based indexing is used (hence, the first element will always be zero).
-          For example, if the 'external_file' dataset has three paths to files and
-          the first file has 5 frames, the second file has 10 frames, and the third
-          file has 20 frames, then this attribute will have values [0, 5, 15]. If
-          there is a single external file that holds all of the frames of the ImageSeries
-          (and so there is a single element in the 'external_file' dataset), then
-          this attribute should have value [0].
-        range: int32
-      external_file:
-        name: external_file
-        description: Paths to one or more external file(s). The field is only present
-          if format='external'. This is only relevant if the image series is stored
-          in the file system as one or more image file(s). This field should NOT be
-          used if the image is stored in another NWB file and that file is linked
-          to this file.
-        multivalued: true
-        range: text
-        required: false
   OpticalSeries__field_of_view:
     name: OpticalSeries__field_of_view
     description: Width, height and depth of image, or imaged area, in meters.
     attributes:
+      name:
+        name: name
+        ifabsent: string(field_of_view)
+        range: string
+        required: true
+        equals_string: field_of_view
       array:
         name: array
         range: OpticalSeries__field_of_view__Array
@@ -153,6 +123,12 @@ classes:
     name: OpticalSeries__data
     description: Images presented to subject, either grayscale or RGB
     attributes:
+      name:
+        name: name
+        ifabsent: string(data)
+        range: string
+        required: true
+        equals_string: data
       array:
         name: array
         range: OpticalSeries__data__Array
@@ -178,30 +154,3 @@ classes:
         required: false
         minimum_cardinality: 3
         maximum_cardinality: 3
-  IndexSeries__data:
-    name: IndexSeries__data
-    description: Index of the image (using zero-indexing) in the linked Images object.
-    attributes:
-      conversion:
-        name: conversion
-        description: This field is unused by IndexSeries.
-        range: float32
-      resolution:
-        name: resolution
-        description: This field is unused by IndexSeries.
-        range: float32
-      offset:
-        name: offset
-        description: This field is unused by IndexSeries.
-        range: float32
-      unit:
-        name: unit
-        description: This field is unused by IndexSeries and has the value N/A.
-        range: text
-      data:
-        name: data
-        description: Index of the image (using zero-indexing) in the linked Images
-          object.
-        multivalued: true
-        range: uint32
-        required: true

nwb_linkml/schema/core.nwb.image.yaml

@@ -13,25 +13,40 @@ classes:
     description: A grayscale image.
     is_a: Image
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       array:
         name: array
         range: GrayscaleImage__Array
+    tree_root: true
   RGBImage:
     name: RGBImage
     description: A color image.
     is_a: Image
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       array:
         name: array
         range: RGBImage__Array
+    tree_root: true
   RGBAImage:
     name: RGBAImage
     description: A color image with transparency.
     is_a: Image
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       array:
         name: array
         range: RGBAImage__Array
+    tree_root: true
   ImageSeries:
     name: ImageSeries
     description: General image data that is common between acquisition and stimulus
@@ -42,6 +57,10 @@ classes:
       stack. [frame][x][y] or [frame][x][y][z].
     is_a: TimeSeries
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       data:
         name: data
         description: Binary data representing images across frames. If data are stored
@@ -52,8 +71,8 @@ classes:
       dimension:
         name: dimension
         description: Number of pixels on x, y, (and z) axes.
-        multivalued: false
-        range: ImageSeries__dimension
+        multivalued: true
+        range: int32
         required: false
       external_file:
         name: external_file
@@ -62,8 +81,8 @@ classes:
           in the file system as one or more image file(s). This field should NOT be
           used if the image is stored in another NWB file and that file is linked
           to this file.
-        multivalued: false
-        range: ImageSeries__external_file
+        multivalued: true
+        range: text
         required: false
       format:
         name: format
@@ -74,6 +93,7 @@ classes:
         multivalued: false
         range: text
         required: false
+    tree_root: true
   ImageMaskSeries:
     name: ImageMaskSeries
     description: An alpha mask that is applied to a presented visual stimulus. The
@@ -82,6 +102,12 @@ classes:
       array indicates the starting time of a mask, and that mask pattern continues
       until it's explicitly changed.
     is_a: ImageSeries
+    attributes:
+      name:
+        name: name
+        range: string
+        required: true
+    tree_root: true
   OpticalSeries:
     name: OpticalSeries
     description: Image data that is presented or recorded. A stimulus template movie
@@ -91,6 +117,10 @@ classes:
       OpticalSeries represents acquired imaging data, orientation is also important.
     is_a: ImageSeries
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       distance:
         name: distance
         description: Distance from camera/monitor to target/eye.
@@ -116,6 +146,7 @@ classes:
         multivalued: false
         range: text
         required: false
+    tree_root: true
   IndexSeries:
     name: IndexSeries
     description: Stores indices to image frames stored in an ImageSeries. The purpose
@@ -127,10 +158,15 @@ classes:
       was displayed.
     is_a: TimeSeries
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       data:
         name: data
         description: Index of the image (using zero-indexing) in the linked Images
           object.
-        multivalued: false
-        range: IndexSeries__data
+        multivalued: true
+        range: uint32
         required: true
+    tree_root: true

nwb_linkml/schema/core.nwb.misc.include.yaml

@@ -13,6 +13,12 @@ classes:
     name: AbstractFeatureSeries__data
     description: Values of each feature at each time.
     attributes:
+      name:
+        name: name
+        ifabsent: string(data)
+        range: string
+        required: true
+        equals_string: data
       unit:
         name: unit
         description: Since there can be different units for different features, store
@@ -34,70 +40,16 @@ classes:
         name: num_features
         range: numeric
         required: false
-  AbstractFeatureSeries__feature_units:
-    name: AbstractFeatureSeries__feature_units
-    description: Units of each feature.
-    attributes:
-      feature_units:
-        name: feature_units
-        description: Units of each feature.
-        multivalued: true
-        range: text
-        required: false
-  AbstractFeatureSeries__features:
-    name: AbstractFeatureSeries__features
-    description: Description of the features represented in TimeSeries::data.
-    attributes:
-      features:
-        name: features
-        description: Description of the features represented in TimeSeries::data.
-        multivalued: true
-        range: text
-        required: true
-  AnnotationSeries__data:
-    name: AnnotationSeries__data
-    description: Annotations made during an experiment.
-    attributes:
-      resolution:
-        name: resolution
-        description: Smallest meaningful difference between values in data. Annotations
-          have no units, so the value is fixed to -1.0.
-        range: float32
-      unit:
-        name: unit
-        description: Base unit of measurement for working with the data. Annotations
-          have no units, so the value is fixed to 'n/a'.
-        range: text
-      data:
-        name: data
-        description: Annotations made during an experiment.
-        multivalued: true
-        range: text
-        required: true
-  IntervalSeries__data:
-    name: IntervalSeries__data
-    description: Use values >0 if interval started, <0 if interval ended.
-    attributes:
-      resolution:
-        name: resolution
-        description: Smallest meaningful difference between values in data. Annotations
-          have no units, so the value is fixed to -1.0.
-        range: float32
-      unit:
-        name: unit
-        description: Base unit of measurement for working with the data. Annotations
-          have no units, so the value is fixed to 'n/a'.
-        range: text
-      data:
-        name: data
-        description: Use values >0 if interval started, <0 if interval ended.
-        multivalued: true
-        range: int8
-        required: true
   DecompositionSeries__data:
     name: DecompositionSeries__data
     description: Data decomposed into frequency bands.
     attributes:
+      name:
+        name: name
+        ifabsent: string(data)
+        range: string
+        required: true
+        equals_string: data
       unit:
         name: unit
         description: Base unit of measurement for working with the data. Actual stored
@@ -114,72 +66,49 @@ classes:
       num_times:
         name: num_times
         range: numeric
-        required: false
+        required: true
       num_channels:
         name: num_channels
         range: numeric
-        required: false
+        required: true
       num_bands:
         name: num_bands
         range: numeric
-        required: false
+        required: true
   DecompositionSeries__source_channels:
     name: DecompositionSeries__source_channels
     description: DynamicTableRegion pointer to the channels that this decomposition
       series was generated from.
     is_a: DynamicTableRegion
-  DecompositionSeries__bands:
-    name: DecompositionSeries__bands
-    description: Table for describing the bands that this series was generated from.
-      There should be one row in this table for each band.
-    is_a: DynamicTable
     attributes:
-      band_name:
-        name: band_name
-        description: Name of the band, e.g. theta.
-        multivalued: true
-        range: text
-      band_limits:
-        name: band_limits
-        description: Low and high limit of each band in Hz. If it is a Gaussian filter,
-          use 2 SD on either side of the center.
-        multivalued: false
-        range: DecompositionSeries__bands__band_limits
+      name:
+        name: name
+        ifabsent: string(source_channels)
+        range: string
         required: true
-      band_mean:
-        name: band_mean
-        description: The mean Gaussian filters, in Hz.
-        multivalued: false
-        range: DecompositionSeries__bands__band_mean
-        required: true
-      band_stdev:
-        name: band_stdev
-        description: The standard deviation of Gaussian filters, in Hz.
-        multivalued: false
-        range: DecompositionSeries__bands__band_stdev
-        required: true
-  DecompositionSeries__bands__band_limits:
-    name: DecompositionSeries__bands__band_limits
-    description: Low and high limit of each band in Hz. If it is a Gaussian filter,
-      use 2 SD on either side of the center.
-    is_a: VectorData
-  DecompositionSeries__bands__band_mean:
-    name: DecompositionSeries__bands__band_mean
-    description: The mean Gaussian filters, in Hz.
-    is_a: VectorData
-  DecompositionSeries__bands__band_stdev:
-    name: DecompositionSeries__bands__band_stdev
-    description: The standard deviation of Gaussian filters, in Hz.
-    is_a: VectorData
+        equals_string: source_channels
   Units__spike_times_index:
     name: Units__spike_times_index
     description: Index into the spike_times dataset.
     is_a: VectorIndex
+    attributes:
+      name:
+        name: name
+        ifabsent: string(spike_times_index)
+        range: string
+        required: true
+        equals_string: spike_times_index
   Units__spike_times:
     name: Units__spike_times
     description: Spike times for each unit in seconds.
     is_a: VectorData
     attributes:
+      name:
+        name: name
+        ifabsent: string(spike_times)
+        range: string
+        required: true
+        equals_string: spike_times
       resolution:
         name: resolution
         description: The smallest possible difference between two spike times. Usually
@@ -192,23 +121,57 @@ classes:
     name: Units__obs_intervals_index
     description: Index into the obs_intervals dataset.
     is_a: VectorIndex
+    attributes:
+      name:
+        name: name
+        ifabsent: string(obs_intervals_index)
+        range: string
+        required: true
+        equals_string: obs_intervals_index
   Units__obs_intervals:
     name: Units__obs_intervals
     description: Observation intervals for each unit.
     is_a: VectorData
+    attributes:
+      name:
+        name: name
+        ifabsent: string(obs_intervals)
+        range: string
+        required: true
+        equals_string: obs_intervals
   Units__electrodes_index:
     name: Units__electrodes_index
     description: Index into electrodes.
     is_a: VectorIndex
+    attributes:
+      name:
+        name: name
+        ifabsent: string(electrodes_index)
+        range: string
+        required: true
+        equals_string: electrodes_index
   Units__electrodes:
     name: Units__electrodes
     description: Electrode that each spike unit came from, specified using a DynamicTableRegion.
     is_a: DynamicTableRegion
+    attributes:
+      name:
+        name: name
+        ifabsent: string(electrodes)
+        range: string
+        required: true
+        equals_string: electrodes
   Units__waveform_mean:
     name: Units__waveform_mean
     description: Spike waveform mean for each spike unit.
     is_a: VectorData
     attributes:
+      name:
+        name: name
+        ifabsent: string(waveform_mean)
+        range: string
+        required: true
+        equals_string: waveform_mean
       sampling_rate:
         name: sampling_rate
         description: Sampling rate, in hertz.
@@ -222,6 +185,12 @@ classes:
     description: Spike waveform standard deviation for each spike unit.
     is_a: VectorData
     attributes:
+      name:
+        name: name
+        ifabsent: string(waveform_sd)
+        range: string
+        required: true
+        equals_string: waveform_sd
       sampling_rate:
         name: sampling_rate
         description: Sampling rate, in hertz.
@@ -257,6 +226,12 @@ classes:
       each waveform must be the same.
     is_a: VectorData
     attributes:
+      name:
+        name: name
+        ifabsent: string(waveforms)
+        range: string
+        required: true
+        equals_string: waveforms
       sampling_rate:
         name: sampling_rate
         description: Sampling rate, in hertz.
@@ -270,8 +245,22 @@ classes:
     description: Index into the waveforms dataset. One value for every spike event.
       See 'waveforms' for more detail.
     is_a: VectorIndex
+    attributes:
+      name:
+        name: name
+        ifabsent: string(waveforms_index)
+        range: string
+        required: true
+        equals_string: waveforms_index
   Units__waveforms_index_index:
     name: Units__waveforms_index_index
     description: Index into the waveforms_index dataset. One value for every unit
       (row in the table). See 'waveforms' for more detail.
     is_a: VectorIndex
+    attributes:
+      name:
+        name: name
+        ifabsent: string(waveforms_index_index)
+        range: string
+        required: true
+        equals_string: waveforms_index_index

nwb_linkml/schema/core.nwb.misc.yaml

@@ -22,6 +22,10 @@ classes:
       is impractical.
     is_a: TimeSeries
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       data:
         name: data
         description: Values of each feature at each time.
@@ -31,15 +35,16 @@ classes:
       feature_units:
         name: feature_units
         description: Units of each feature.
-        multivalued: false
-        range: AbstractFeatureSeries__feature_units
+        multivalued: true
+        range: text
         required: false
       features:
         name: features
         description: Description of the features represented in TimeSeries::data.
-        multivalued: false
-        range: AbstractFeatureSeries__features
+        multivalued: true
+        range: text
         required: true
+    tree_root: true
   AnnotationSeries:
     name: AnnotationSeries
     description: Stores user annotations made during an experiment. The data[] field
@@ -48,12 +53,17 @@ classes:
       is identifiable as storing annotations in a machine-readable way.
     is_a: TimeSeries
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       data:
         name: data
         description: Annotations made during an experiment.
-        multivalued: false
-        range: AnnotationSeries__data
+        multivalued: true
+        range: text
         required: true
+    tree_root: true
   IntervalSeries:
     name: IntervalSeries
     description: Stores intervals of data. The timestamps field stores the beginning
@@ -65,17 +75,26 @@ classes:
       time intervals in a machine-readable way.
     is_a: TimeSeries
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       data:
         name: data
         description: Use values >0 if interval started, <0 if interval ended.
-        multivalued: false
-        range: IntervalSeries__data
+        multivalued: true
+        range: int8
         required: true
+    tree_root: true
   DecompositionSeries:
     name: DecompositionSeries
     description: Spectral analysis of a time series, e.g. of an LFP or a speech signal.
     is_a: TimeSeries
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       data:
         name: data
         description: Data decomposed into frequency bands.
@@ -100,14 +119,19 @@ classes:
         description: Table for describing the bands that this series was generated
           from. There should be one row in this table for each band.
         multivalued: false
-        range: DecompositionSeries__bands
+        range: DynamicTable
         required: true
+    tree_root: true
   Units:
     name: Units
     description: Data about spiking units. Event times of observed units (e.g. cell,
       synapse, etc.) should be concatenated and stored in spike_times.
     is_a: DynamicTable
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       spike_times_index:
         name: spike_times_index
         description: Index into the spike_times dataset.
@@ -203,3 +227,4 @@ classes:
         multivalued: false
         range: Units__waveforms_index_index
         required: false
+    tree_root: true

nwb_linkml/schema/core.nwb.ogen.include.yaml

@@ -1,24 +0,0 @@
-name: core.nwb.ogen.include
-id: core.nwb.ogen.include
-imports:
-- core.nwb.base
-- core.nwb.device
-- nwb.language
-- core.nwb.ogen.include
-- core.nwb.ogen
-default_prefix: core.nwb.ogen.include/
-classes:
-  OptogeneticSeries__data:
-    name: OptogeneticSeries__data
-    description: Applied power for optogenetic stimulus, in watts.
-    attributes:
-      unit:
-        name: unit
-        description: Unit of measurement for data, which is fixed to 'watts'.
-        range: text
-      data:
-        name: data
-        description: Applied power for optogenetic stimulus, in watts.
-        multivalued: true
-        range: numeric
-        required: true

nwb_linkml/schema/core.nwb.ogen.yaml

@@ -4,7 +4,6 @@ imports:
 - core.nwb.base
 - core.nwb.device
 - nwb.language
-- core.nwb.ogen.include
 - core.nwb.ogen
 default_prefix: core.nwb.ogen/
 classes:
@@ -13,17 +12,26 @@ classes:
     description: An optogenetic stimulus.
     is_a: TimeSeries
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       data:
         name: data
         description: Applied power for optogenetic stimulus, in watts.
-        multivalued: false
-        range: OptogeneticSeries__data
+        multivalued: true
+        range: numeric
         required: true
+    tree_root: true
   OptogeneticStimulusSite:
     name: OptogeneticStimulusSite
     description: A site of optogenetic stimulation.
     is_a: NWBContainer
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       description:
         name: description
         description: Description of stimulation site.
@@ -44,3 +52,4 @@ classes:
         multivalued: false
         range: text
         required: true
+    tree_root: true

nwb_linkml/schema/core.nwb.ophys.include.yaml

@@ -14,6 +14,12 @@ classes:
     name: TwoPhotonSeries__field_of_view
     description: Width, height and depth of image, or imaged area, in meters.
     attributes:
+      name:
+        name: name
+        ifabsent: string(field_of_view)
+        range: string
+        required: true
+        equals_string: field_of_view
       array:
         name: array
         range: TwoPhotonSeries__field_of_view__Array
@@ -37,6 +43,12 @@ classes:
     name: RoiResponseSeries__data
     description: Signals from ROIs.
     attributes:
+      name:
+        name: name
+        ifabsent: string(data)
+        range: string
+        required: true
+        equals_string: data
       array:
         name: array
         range: RoiResponseSeries__data__Array
@@ -57,36 +69,59 @@ classes:
     description: DynamicTableRegion referencing into an ROITable containing information
       on the ROIs stored in this timeseries.
     is_a: DynamicTableRegion
+    attributes:
+      name:
+        name: name
+        ifabsent: string(rois)
+        range: string
+        required: true
+        equals_string: rois
   PlaneSegmentation__image_mask:
     name: PlaneSegmentation__image_mask
     description: ROI masks for each ROI. Each image mask is the size of the original
       imaging plane (or volume) and members of the ROI are finite non-zero.
     is_a: VectorData
+    attributes:
+      name:
+        name: name
+        ifabsent: string(image_mask)
+        range: string
+        required: true
+        equals_string: image_mask
   PlaneSegmentation__pixel_mask_index:
     name: PlaneSegmentation__pixel_mask_index
     description: Index into pixel_mask.
     is_a: VectorIndex
+    attributes:
+      name:
+        name: name
+        ifabsent: string(pixel_mask_index)
+        range: string
+        required: true
+        equals_string: pixel_mask_index
   PlaneSegmentation__voxel_mask_index:
     name: PlaneSegmentation__voxel_mask_index
     description: Index into voxel_mask.
     is_a: VectorIndex
-  PlaneSegmentation__reference_images:
-    name: PlaneSegmentation__reference_images
-    description: Image stacks that the segmentation masks apply to.
     attributes:
-      ImageSeries:
-        name: ImageSeries
-        description: One or more image stacks that the masks apply to (can be one-element
-          stack).
-        multivalued: true
-        range: ImageSeries
-        required: false
+      name:
+        name: name
+        ifabsent: string(voxel_mask_index)
+        range: string
+        required: true
+        equals_string: voxel_mask_index
   ImagingPlane__manifold:
     name: ImagingPlane__manifold
     description: DEPRECATED Physical position of each pixel. 'xyz' represents the
       position of the pixel relative to the defined coordinate space. Deprecated in
       favor of origin_coords and grid_spacing.
     attributes:
+      name:
+        name: name
+        ifabsent: string(manifold)
+        range: string
+        required: true
+        equals_string: manifold
       conversion:
         name: conversion
         description: Scalar to multiply each element in data to convert it to the
@@ -134,6 +169,12 @@ classes:
       for 2-D data or (0, 0, 0) for 3-D data. See also reference_frame for what the
       physical location is relative to (e.g., bregma).
     attributes:
+      name:
+        name: name
+        ifabsent: string(origin_coords)
+        range: string
+        required: true
+        equals_string: origin_coords
       unit:
         name: unit
         description: Measurement units for origin_coords. The default value is 'meters'.
@@ -163,6 +204,12 @@ classes:
       in the specified unit. Assumes imaging plane is a regular grid. See also reference_frame
       to interpret the grid.
     attributes:
+      name:
+        name: name
+        ifabsent: string(grid_spacing)
+        range: string
+        required: true
+        equals_string: grid_spacing
       unit:
         name: unit
         description: Measurement units for grid_spacing. The default value is 'meters'.
@@ -186,12 +233,3 @@ classes:
         required: false
         minimum_cardinality: 3
         maximum_cardinality: 3
-  CorrectedImageStack__corrected:
-    name: CorrectedImageStack__corrected
-    description: Image stack with frames shifted to the common coordinates.
-    is_a: ImageSeries
-  CorrectedImageStack__xy_translation:
-    name: CorrectedImageStack__xy_translation
-    description: Stores the x,y delta necessary to align each frame to the common
-      coordinates, for example, to align each frame to a reference image.
-    is_a: TimeSeries

nwb_linkml/schema/core.nwb.ophys.yaml

@@ -15,6 +15,10 @@ classes:
     description: Image stack recorded over time from 1-photon microscope.
     is_a: ImageSeries
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       pmt_gain:
         name: pmt_gain
         description: Photomultiplier gain.
@@ -41,11 +45,16 @@ classes:
         name: intensity
         description: Intensity of the excitation in mW/mm^2, if known.
         range: float32
+    tree_root: true
   TwoPhotonSeries:
     name: TwoPhotonSeries
     description: Image stack recorded over time from 2-photon microscope.
     is_a: ImageSeries
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       pmt_gain:
         name: pmt_gain
         description: Photomultiplier gain.
@@ -62,12 +71,17 @@ classes:
         multivalued: false
         range: TwoPhotonSeries__field_of_view
         required: false
+    tree_root: true
   RoiResponseSeries:
     name: RoiResponseSeries
     description: ROI responses over an imaging plane. The first dimension represents
       time. The second dimension, if present, represents ROIs.
     is_a: TimeSeries
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       data:
         name: data
         description: Signals from ROIs.
@@ -81,6 +95,7 @@ classes:
         multivalued: false
         range: RoiResponseSeries__rois
         required: true
+    tree_root: true
   DfOverF:
     name: DfOverF
     description: dF/F information about a region of interest (ROI). Storage hierarchy
@@ -88,12 +103,17 @@ classes:
       for image planes).
     is_a: NWBDataInterface
     attributes:
-      RoiResponseSeries:
-        name: RoiResponseSeries
+      name:
+        name: name
+        range: string
+        required: true
+      roi_response_series:
+        name: roi_response_series
         description: RoiResponseSeries object(s) containing dF/F for a ROI.
         multivalued: true
         range: RoiResponseSeries
         required: true
+    tree_root: true
   Fluorescence:
     name: Fluorescence
     description: Fluorescence information about a region of interest (ROI). Storage
@@ -101,13 +121,18 @@ classes:
       for ROIs and for image planes).
     is_a: NWBDataInterface
     attributes:
-      RoiResponseSeries:
-        name: RoiResponseSeries
+      name:
+        name: name
+        range: string
+        required: true
+      roi_response_series:
+        name: roi_response_series
         description: RoiResponseSeries object(s) containing fluorescence data for
           a ROI.
         multivalued: true
         range: RoiResponseSeries
         required: true
+    tree_root: true
   ImageSegmentation:
     name: ImageSegmentation
     description: Stores pixels in an image that represent different regions of interest
@@ -119,17 +144,26 @@ classes:
       is required and ROI names should remain consistent between them.
     is_a: NWBDataInterface
     attributes:
-      PlaneSegmentation:
-        name: PlaneSegmentation
+      name:
+        name: name
+        range: string
+        required: true
+      plane_segmentation:
+        name: plane_segmentation
         description: Results from image segmentation of a specific imaging plane.
         multivalued: true
         range: PlaneSegmentation
         required: true
+    tree_root: true
   PlaneSegmentation:
     name: PlaneSegmentation
     description: Results from image segmentation of a specific imaging plane.
     is_a: DynamicTable
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       image_mask:
         name: image_mask
         description: ROI masks for each ROI. Each image mask is the size of the original
@@ -166,14 +200,19 @@ classes:
       reference_images:
         name: reference_images
         description: Image stacks that the segmentation masks apply to.
-        multivalued: false
-        range: PlaneSegmentation__reference_images
-        required: true
+        multivalued: true
+        any_of:
+        - range: ImageSeries
+    tree_root: true
   ImagingPlane:
     name: ImagingPlane
     description: An imaging plane and its metadata.
     is_a: NWBContainer
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       description:
         name: description
         description: Description of the imaging plane.
@@ -253,17 +292,22 @@ classes:
         multivalued: false
         range: text
         required: false
-      OpticalChannel:
-        name: OpticalChannel
+      optical_channel:
+        name: optical_channel
         description: An optical channel used to record from an imaging plane.
         multivalued: true
         range: OpticalChannel
         required: true
+    tree_root: true
   OpticalChannel:
     name: OpticalChannel
     description: An optical channel used to record from an imaging plane.
     is_a: NWBContainer
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       description:
         name: description
         description: Description or other notes about the channel.
@@ -276,6 +320,7 @@ classes:
         multivalued: false
         range: float32
         required: true
+    tree_root: true
   MotionCorrection:
     name: MotionCorrection
     description: 'An image stack where all frames are shifted (registered) to a common
@@ -283,27 +328,37 @@ classes:
       frame at each point in time is assumed to be 2-D (has only x & y dimensions).'
     is_a: NWBDataInterface
     attributes:
-      CorrectedImageStack:
-        name: CorrectedImageStack
+      name:
+        name: name
+        range: string
+        required: true
+      corrected_image_stack:
+        name: corrected_image_stack
         description: Reuslts from motion correction of an image stack.
         multivalued: true
         range: CorrectedImageStack
         required: true
+    tree_root: true
   CorrectedImageStack:
     name: CorrectedImageStack
     description: Reuslts from motion correction of an image stack.
     is_a: NWBDataInterface
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       corrected:
         name: corrected
         description: Image stack with frames shifted to the common coordinates.
         multivalued: false
-        range: CorrectedImageStack__corrected
+        range: ImageSeries
         required: true
       xy_translation:
         name: xy_translation
         description: Stores the x,y delta necessary to align each frame to the common
           coordinates, for example, to align each frame to a reference image.
         multivalued: false
-        range: CorrectedImageStack__xy_translation
+        range: TimeSeries
         required: true
+    tree_root: true

nwb_linkml/schema/core.nwb.retinotopy.include.yaml

@@ -11,6 +11,12 @@ classes:
     name: ImagingRetinotopy__axis_1_phase_map
     description: Phase response to stimulus on the first measured axis.
     attributes:
+      name:
+        name: name
+        ifabsent: string(axis_1_phase_map)
+        range: string
+        required: true
+        equals_string: axis_1_phase_map
       dimension:
         name: dimension
         description: 'Number of rows and columns in the image. NOTE: row, column representation
@@ -34,16 +40,22 @@ classes:
       num_rows:
         name: num_rows
         range: float32
-        required: false
+        required: true
       num_cols:
         name: num_cols
         range: float32
-        required: false
+        required: true
   ImagingRetinotopy__axis_1_power_map:
     name: ImagingRetinotopy__axis_1_power_map
     description: Power response on the first measured axis. Response is scaled so
       0.0 is no power in the response and 1.0 is maximum relative power.
     attributes:
+      name:
+        name: name
+        ifabsent: string(axis_1_power_map)
+        range: string
+        required: true
+        equals_string: axis_1_power_map
       dimension:
         name: dimension
         description: 'Number of rows and columns in the image. NOTE: row, column representation
@@ -67,15 +79,21 @@ classes:
       num_rows:
         name: num_rows
         range: float32
-        required: false
+        required: true
       num_cols:
         name: num_cols
         range: float32
-        required: false
+        required: true
   ImagingRetinotopy__axis_2_phase_map:
     name: ImagingRetinotopy__axis_2_phase_map
     description: Phase response to stimulus on the second measured axis.
     attributes:
+      name:
+        name: name
+        ifabsent: string(axis_2_phase_map)
+        range: string
+        required: true
+        equals_string: axis_2_phase_map
       dimension:
         name: dimension
         description: 'Number of rows and columns in the image. NOTE: row, column representation
@@ -99,16 +117,22 @@ classes:
       num_rows:
         name: num_rows
         range: float32
-        required: false
+        required: true
       num_cols:
         name: num_cols
         range: float32
-        required: false
+        required: true
   ImagingRetinotopy__axis_2_power_map:
     name: ImagingRetinotopy__axis_2_power_map
     description: Power response on the second measured axis. Response is scaled so
       0.0 is no power in the response and 1.0 is maximum relative power.
     attributes:
+      name:
+        name: name
+        ifabsent: string(axis_2_power_map)
+        range: string
+        required: true
+        equals_string: axis_2_power_map
       dimension:
         name: dimension
         description: 'Number of rows and columns in the image. NOTE: row, column representation
@@ -132,30 +156,22 @@ classes:
       num_rows:
         name: num_rows
         range: float32
-        required: false
+        required: true
       num_cols:
         name: num_cols
         range: float32
-        required: false
-  ImagingRetinotopy__axis_descriptions:
-    name: ImagingRetinotopy__axis_descriptions
-    description: Two-element array describing the contents of the two response axis
-      fields. Description should be something like ['altitude', 'azimuth'] or '['radius',
-      'theta'].
-    attributes:
-      axis_descriptions:
-        name: axis_descriptions
-        description: Two-element array describing the contents of the two response
-          axis fields. Description should be something like ['altitude', 'azimuth']
-          or '['radius', 'theta'].
-        multivalued: true
-        range: text
         required: true
   ImagingRetinotopy__focal_depth_image:
     name: ImagingRetinotopy__focal_depth_image
     description: 'Gray-scale image taken with same settings/parameters (e.g., focal
       depth, wavelength) as data collection. Array format: [rows][columns].'
     attributes:
+      name:
+        name: name
+        ifabsent: string(focal_depth_image)
+        range: string
+        required: true
+        equals_string: focal_depth_image
       bits_per_pixel:
         name: bits_per_pixel
         description: Number of bits used to represent each value. This is necessary
@@ -188,16 +204,22 @@ classes:
       num_rows:
         name: num_rows
         range: uint16
-        required: false
+        required: true
       num_cols:
         name: num_cols
         range: uint16
-        required: false
+        required: true
   ImagingRetinotopy__sign_map:
     name: ImagingRetinotopy__sign_map
     description: Sine of the angle between the direction of the gradient in axis_1
       and axis_2.
     attributes:
+      name:
+        name: name
+        ifabsent: string(sign_map)
+        range: string
+        required: true
+        equals_string: sign_map
       dimension:
         name: dimension
         description: 'Number of rows and columns in the image. NOTE: row, column representation
@@ -217,16 +239,22 @@ classes:
       num_rows:
         name: num_rows
         range: float32
-        required: false
+        required: true
       num_cols:
         name: num_cols
         range: float32
-        required: false
+        required: true
   ImagingRetinotopy__vasculature_image:
     name: ImagingRetinotopy__vasculature_image
     description: 'Gray-scale anatomical image of cortical surface. Array structure:
       [rows][columns]'
     attributes:
+      name:
+        name: name
+        ifabsent: string(vasculature_image)
+        range: string
+        required: true
+        equals_string: vasculature_image
       bits_per_pixel:
         name: bits_per_pixel
         description: Number of bits used to represent each value. This is necessary
@@ -255,8 +283,8 @@ classes:
       num_rows:
         name: num_rows
         range: uint16
-        required: false
+        required: true
       num_cols:
         name: num_cols
         range: uint16
-        required: false
+        required: true

nwb_linkml/schema/core.nwb.retinotopy.yaml

@@ -20,6 +20,10 @@ classes:
       appear backward (i.e., y before x).'
     is_a: NWBDataInterface
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       axis_1_phase_map:
         name: axis_1_phase_map
         description: Phase response to stimulus on the first measured axis.
@@ -51,8 +55,8 @@ classes:
         description: Two-element array describing the contents of the two response
           axis fields. Description should be something like ['altitude', 'azimuth']
           or '['radius', 'theta'].
-        multivalued: false
-        range: ImagingRetinotopy__axis_descriptions
+        multivalued: true
+        range: text
         required: true
       focal_depth_image:
         name: focal_depth_image
@@ -75,3 +79,4 @@ classes:
         multivalued: false
         range: ImagingRetinotopy__vasculature_image
         required: true
+    tree_root: true

nwb_linkml/schema/hdmf-common.base.include.yaml

@@ -1,7 +0,0 @@
-name: hdmf-common.base.include
-id: hdmf-common.base.include
-imports:
-- nwb.language
-- hdmf-common.base.include
-- hdmf-common.base
-default_prefix: hdmf-common.base.include/

nwb_linkml/schema/hdmf-common.base.yaml

@@ -2,31 +2,47 @@ name: hdmf-common.base
 id: hdmf-common.base
 imports:
 - nwb.language
-- hdmf-common.base.include
 - hdmf-common.base
 default_prefix: hdmf-common.base/
 classes:
   Data:
     name: Data
     description: An abstract data type for a dataset.
+    attributes:
+      name:
+        name: name
+        range: string
+        required: true
+    tree_root: true
   Container:
     name: Container
     description: An abstract data type for a group storing collections of data and
       metadata. Base type for all data and metadata containers.
+    attributes:
+      name:
+        name: name
+        range: string
+        required: true
+    tree_root: true
   SimpleMultiContainer:
     name: SimpleMultiContainer
     description: A simple Container for holding onto multiple containers.
     is_a: Container
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       Data:
         name: Data
         description: Data objects held within this SimpleMultiContainer.
         multivalued: true
         range: Data
         required: false
-      Container:
-        name: Container
+      container:
+        name: container
         description: Container objects held within this SimpleMultiContainer.
         multivalued: true
         range: Container
         required: false
+    tree_root: true

nwb_linkml/schema/hdmf-common.sparse.include.yaml

@@ -1,39 +0,0 @@
-name: hdmf-common.sparse.include
-id: hdmf-common.sparse.include
-imports:
-- hdmf-common.base
-- nwb.language
-- hdmf-common.sparse.include
-- hdmf-common.sparse
-default_prefix: hdmf-common.sparse.include/
-classes:
-  CSRMatrix__indices:
-    name: CSRMatrix__indices
-    description: The column indices.
-    attributes:
-      indices:
-        name: indices
-        description: The column indices.
-        multivalued: true
-        range: uint
-        required: true
-  CSRMatrix__indptr:
-    name: CSRMatrix__indptr
-    description: The row index pointer.
-    attributes:
-      indptr:
-        name: indptr
-        description: The row index pointer.
-        multivalued: true
-        range: uint
-        required: true
-  CSRMatrix__data:
-    name: CSRMatrix__data
-    description: The non-zero values in the matrix.
-    attributes:
-      data:
-        name: data
-        description: The non-zero values in the matrix.
-        multivalued: true
-        range: AnyType
-        required: true

nwb_linkml/schema/hdmf-common.sparse.yaml

@@ -3,7 +3,6 @@ id: hdmf-common.sparse
 imports:
 - hdmf-common.base
 - nwb.language
-- hdmf-common.sparse.include
 - hdmf-common.sparse
 default_prefix: hdmf-common.sparse/
 classes:
@@ -14,6 +13,10 @@ classes:
       and their corresponding values are stored in data[indptr[i]:indptr[i+1]].
     is_a: Container
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       shape:
         name: shape
         description: The shape (number of rows, number of columns) of this sparse
@@ -22,18 +25,19 @@ classes:
       indices:
         name: indices
         description: The column indices.
-        multivalued: false
-        range: CSRMatrix__indices
+        multivalued: true
+        range: uint
         required: true
       indptr:
         name: indptr
         description: The row index pointer.
-        multivalued: false
-        range: CSRMatrix__indptr
+        multivalued: true
+        range: uint
         required: true
       data:
         name: data
         description: The non-zero values in the matrix.
-        multivalued: false
-        range: CSRMatrix__data
+        multivalued: true
+        range: AnyType
         required: true
+    tree_root: true

nwb_linkml/schema/hdmf-common.table.include.yaml

@@ -35,14 +35,3 @@ classes:
         name: num_elements
         range: int
         required: true
-  DynamicTable__id:
-    name: DynamicTable__id
-    description: Array of unique identifiers for the rows of this dynamic table.
-    is_a: ElementIdentifiers
-    attributes:
-      id:
-        name: id
-        description: Array of unique identifiers for the rows of this dynamic table.
-        multivalued: true
-        range: int
-        required: true

nwb_linkml/schema/hdmf-common.table.yaml

@@ -19,6 +19,10 @@ classes:
       and so on.
     is_a: Data
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       description:
         name: description
         description: Description of what these vectors represent.
@@ -26,6 +30,7 @@ classes:
       array:
         name: array
         range: VectorData__Array
+    tree_root: true
   VectorIndex:
     name: VectorIndex
     description: Used with VectorData to encode a ragged array. An array of indices
@@ -35,19 +40,29 @@ classes:
       by "_index".
     is_a: VectorData
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       target:
         name: target
         description: Reference to the target dataset that this index applies to.
         range: VectorData
+    tree_root: true
   ElementIdentifiers:
     name: ElementIdentifiers
     description: A list of unique identifiers for values within a dataset, e.g. rows
       of a DynamicTable.
     is_a: Data
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       array:
         name: array
         range: ElementIdentifiers__Array
+    tree_root: true
   DynamicTableRegion:
     name: DynamicTableRegion
     description: DynamicTableRegion provides a link from one table to an index or
@@ -61,6 +76,10 @@ classes:
       of another `DynamicTable`.
     is_a: VectorData
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       table:
         name: table
         description: Reference to the DynamicTable object that this region applies
@@ -70,6 +89,7 @@ classes:
         name: description
         description: Description of what this table region points to.
         range: text
+    tree_root: true
   DynamicTable:
     name: DynamicTable
     description: A group containing multiple datasets that are aligned on the first
@@ -92,6 +112,10 @@ classes:
       may be an acceptable trade-off for the flexibility of a DynamicTable.
     is_a: Container
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       colnames:
         name: colnames
         description: The names of the columns in this table. This should be used to
@@ -104,8 +128,8 @@ classes:
       id:
         name: id
         description: Array of unique identifiers for the rows of this dynamic table.
-        multivalued: false
-        range: DynamicTable__id
+        multivalued: true
+        range: int
         required: true
       VectorData:
         name: VectorData
@@ -113,6 +137,7 @@ classes:
         multivalued: true
         range: VectorData
         required: false
+    tree_root: true
   AlignedDynamicTable:
     name: AlignedDynamicTable
     description: DynamicTable container that supports storing a collection of sub-tables.
@@ -124,6 +149,10 @@ classes:
       by a separate DynamicTable stored within the group.
     is_a: DynamicTable
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       categories:
         name: categories
         description: The names of the categories in this AlignedDynamicTable. Each
@@ -132,8 +161,8 @@ classes:
           category names must match the names of the corresponding DynamicTable in
           the group.
         range: text
-      DynamicTable:
-        name: DynamicTable
+      dynamic_table:
+        name: dynamic_table
         description: A DynamicTable representing a particular category for columns
           in the AlignedDynamicTable parent container. The table MUST be aligned with
           (i.e., have the same number of rows) as all other DynamicTables stored in
@@ -143,3 +172,4 @@ classes:
         multivalued: true
         range: DynamicTable
         required: false
+    tree_root: true

nwb_linkml/schema/hdmf-experimental.experimental.include.yaml

@@ -1,8 +0,0 @@
-name: hdmf-experimental.experimental.include
-id: hdmf-experimental.experimental.include
-imports:
-- hdmf-common.table
-- nwb.language
-- hdmf-experimental.experimental.include
-- hdmf-experimental.experimental
-default_prefix: hdmf-experimental.experimental.include/

nwb_linkml/schema/hdmf-experimental.experimental.yaml

@@ -3,7 +3,6 @@ id: hdmf-experimental.experimental
 imports:
 - hdmf-common.table
 - nwb.language
-- hdmf-experimental.experimental.include
 - hdmf-experimental.experimental
 default_prefix: hdmf-experimental.experimental/
 classes:
@@ -13,8 +12,13 @@ classes:
       to the i-th value in the VectorData referenced by the 'elements' attribute.
     is_a: VectorData
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       elements:
         name: elements
         description: Reference to the VectorData object that contains the enumerable
           elements
         range: VectorData
+    tree_root: true

nwb_linkml/schema/hdmf-experimental.resources.include.yaml

@@ -1,79 +0,0 @@
-name: hdmf-experimental.resources.include
-id: hdmf-experimental.resources.include
-imports:
-- hdmf-common.base
-- nwb.language
-- hdmf-experimental.resources.include
-- hdmf-experimental.resources
-default_prefix: hdmf-experimental.resources.include/
-classes:
-  HERD__keys:
-    name: HERD__keys
-    description: A table for storing user terms that are used to refer to external
-      resources.
-    is_a: Data
-    attributes:
-      keys:
-        name: keys
-        description: A table for storing user terms that are used to refer to external
-          resources.
-        multivalued: true
-        range: AnyType
-        required: true
-  HERD__files:
-    name: HERD__files
-    description: A table for storing object ids of files used in external resources.
-    is_a: Data
-    attributes:
-      files:
-        name: files
-        description: A table for storing object ids of files used in external resources.
-        multivalued: true
-        range: AnyType
-        required: true
-  HERD__entities:
-    name: HERD__entities
-    description: A table for mapping user terms (i.e., keys) to resource entities.
-    is_a: Data
-    attributes:
-      entities:
-        name: entities
-        description: A table for mapping user terms (i.e., keys) to resource entities.
-        multivalued: true
-        range: AnyType
-        required: true
-  HERD__objects:
-    name: HERD__objects
-    description: A table for identifying which objects in a file contain references
-      to external resources.
-    is_a: Data
-    attributes:
-      objects:
-        name: objects
-        description: A table for identifying which objects in a file contain references
-          to external resources.
-        multivalued: true
-        range: AnyType
-        required: true
-  HERD__object_keys:
-    name: HERD__object_keys
-    description: A table for identifying which objects use which keys.
-    is_a: Data
-    attributes:
-      object_keys:
-        name: object_keys
-        description: A table for identifying which objects use which keys.
-        multivalued: true
-        range: AnyType
-        required: true
-  HERD__entity_keys:
-    name: HERD__entity_keys
-    description: A table for identifying which keys use which entity.
-    is_a: Data
-    attributes:
-      entity_keys:
-        name: entity_keys
-        description: A table for identifying which keys use which entity.
-        multivalued: true
-        range: AnyType
-        required: true

nwb_linkml/schema/hdmf-experimental.resources.yaml

@@ -3,7 +3,6 @@ id: hdmf-experimental.resources
 imports:
 - hdmf-common.base
 - nwb.language
-- hdmf-experimental.resources.include
 - hdmf-experimental.resources
 default_prefix: hdmf-experimental.resources/
 classes:
@@ -13,41 +12,46 @@ classes:
       external resource references in a file or across multiple files.
     is_a: Container
     attributes:
+      name:
+        name: name
+        range: string
+        required: true
       keys:
         name: keys
         description: A table for storing user terms that are used to refer to external
           resources.
-        multivalued: false
-        range: HERD__keys
+        multivalued: true
+        range: AnyType
         required: true
       files:
         name: files
         description: A table for storing object ids of files used in external resources.
-        multivalued: false
-        range: HERD__files
+        multivalued: true
+        range: AnyType
         required: true
       entities:
         name: entities
         description: A table for mapping user terms (i.e., keys) to resource entities.
-        multivalued: false
-        range: HERD__entities
+        multivalued: true
+        range: AnyType
         required: true
       objects:
         name: objects
         description: A table for identifying which objects in a file contain references
           to external resources.
-        multivalued: false
-        range: HERD__objects
+        multivalued: true
+        range: AnyType
         required: true
       object_keys:
         name: object_keys
         description: A table for identifying which objects use which keys.
-        multivalued: false
-        range: HERD__object_keys
+        multivalued: true
+        range: AnyType
         required: true
       entity_keys:
         name: entity_keys
         description: A table for identifying which keys use which entity.
-        multivalued: false
-        range: HERD__entity_keys
+        multivalued: true
+        range: AnyType
         required: true
+    tree_root: true

nwb_linkml/schema/nwb.language.yaml

@@ -85,7 +85,7 @@ types:
     typeof: boolean
   isodatetime:
     name: isodatetime
-    typeof: date
+    typeof: datetime
 enums:
   FlatDType:
     name: FlatDType

pytest.ini

@@ -0,0 +1,4 @@
+[pytest]
+
+testpaths =
+    tests

scripts/generate_core.py

@@ -19,7 +19,7 @@ def generate_core_pydantic(yaml_path:Path, output_path:Path):
 
         generator = NWBPydanticGenerator(
             str(schema),
-            pydantic_version='1',
+            pydantic_version='2',
             emit_metadata=True,
             gen_classvars=True,
             gen_slots=True

tests/test_adapter.py

@@ -0,0 +1,22 @@
+import pytest
+from .fixtures import nwb_core_fixture
+
+from nwb_schema_language import Dataset, Group, Schema
+
+@pytest.mark.parametrize(
+    ['walk_class', 'known_number'],
+    [
+        (Dataset, 211),
+        (Group, 144),
+        ((Dataset, Group), 355),
+        (Schema, 19)
+    ]
+)
+def test_walk_types(nwb_core_fixture, walk_class, known_number):
+    classes = nwb_core_fixture.walk_types(nwb_core_fixture, walk_class)
+    class_list = list(classes)
+    assert len(class_list) == known_number
+
+    # pdb.set_trace()
+
+

tests/test_adapter_dataset.py

@@ -0,0 +1,4 @@
+import pytest
+
+def test_nothing():
+    pass

tests/test_adapter_group.py

@@ -0,0 +1,4 @@
+import pytest
+
+from .fixtures import nwb_core_fixture
+

tests/test_adapter_namespaces.py

@@ -1,19 +1,5 @@
 import pytest
-from rich import print
-import pdb
-
 from .fixtures import nwb_core_fixture
-from nwb_schema_language import Attribute
-
-def test_walk_adapter(nwb_core_fixture):
-    base = nwb_core_fixture.schemas[0]
-    assert base.path.name == "nwb.base.yaml"
-    # type_incs = [inc for inc in base.walk(base)]
-    type_incs = [inc for inc in base.walk_fields(base, 'neurodata_type_inc')]
-
-    attributes = [a for a in base.walk_types(base, Attribute)]
-
-    # pdb.set_trace()
 
 @pytest.mark.parametrize(
     ['class_name','schema_file','namespace_name'],
@@ -32,5 +18,3 @@ def test_find_type_source(nwb_core_fixture, class_name, schema_file, namespace_n
 
 def test_populate_imports(nwb_core_fixture):
     nwb_core_fixture.populate_imports()
-
-    pdb.set_trace()

tests/test_adapter_schema.py

@@ -0,0 +1,14 @@
+import pytest
+from .fixtures import nwb_core_fixture
+
+from nwb_schema_language import Dataset, Group, Schema
+
+@pytest.mark.parametrize(
+    ['schema_name'],
+    [
+        ['core.nwb.file']
+    ]
+)
+def test_schema_build(nwb_core_fixture, schema_name):
+    schema = [sch for sch in nwb_core_fixture.schemas if sch.name == schema_name][0]
+    res = schema.build()

tests/test_adapters/test_adapter_dataset.py

@@ -1 +0,0 @@
-import pytest

tests/test_generate.py

@@ -33,6 +33,8 @@ def test_generate_pydantic(tmp_output_dir):
     (tmp_output_dir / 'models').mkdir(exist_ok=True)
 
     for schema in (tmp_output_dir / 'schema').glob('*.yaml'):
+        if not schema.exists():
+            continue
         # python friendly name
         python_name = schema.stem.replace('.', '_').replace('-','_')