core_nwb_epoch

pydantic model ConfiguredBaseModel

Bases: BaseModel

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

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

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

Config:

  • validate_assignment: bool = True

  • validate_default: bool = True

  • extra: str = forbid

  • arbitrary_types_allowed: bool = True

  • use_enum_values: bool = True

Fields:
field hdf5_path: str | None = None

The absolute path that this object is stored in an NWB file

pydantic model LinkML_Meta

Bases: BaseModel

Extra LinkML Metadata stored as a class attribute

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

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

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

Fields:
field tree_root: bool = False
pydantic model TimeIntervals

Bases: DynamicTable

A container for aggregating epoch data and the TimeSeries that each epoch applies to.

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

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

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

Config:

  • validate_assignment: bool = True

  • validate_default: bool = True

  • extra: str = forbid

  • arbitrary_types_allowed: bool = True

  • use_enum_values: bool = True

Fields:
field colnames: str | None = None

The names of the columns in this table. This should be used to specify an order to the columns.

field description: str | None = None

Description of what is in this dynamic table.

field id: List[int] [Optional]

Array of unique identifiers for the rows of this dynamic table.

field name: str [Required]
field start_time: List[float] | None [Optional]

Start time of epoch, in seconds.

field stop_time: List[float] | None [Optional]

Stop time of epoch, in seconds.

field tags: List[str] | None [Optional]

User-defined tags that identify or categorize events.

field tags_index: TimeIntervalsTagsIndex | None = None

Index for tags.

field timeseries: List[Any] | None [Optional]

An index into a TimeSeries object.

field timeseries_index: TimeIntervalsTimeseriesIndex | None = None

Index for timeseries.

field vector_data: List[VectorData] | None [Optional]

Vector columns, including index columns, of this dynamic table.

linkml_meta: ClassVar[LinkML_Meta] = FieldInfo(annotation=NoneType, required=False, default=LinkML_Meta(tree_root=True), frozen=True)
pydantic model TimeIntervalsTagsIndex

Bases: VectorIndex

Index for tags.

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

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

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

Config:

  • validate_assignment: bool = True

  • validate_default: bool = True

  • extra: str = forbid

  • arbitrary_types_allowed: bool = True

  • use_enum_values: bool = True

Fields:
field array: NDArray[Shape['* dim0'], Any] | NDArray[Shape['* dim0, * dim1'], Any] | NDArray[Shape['* dim0, * dim1, * dim2'], Any] | NDArray[Shape['* dim0, * dim1, * dim2, * dim3'], Any] | None = None
field description: str | None = None

Description of what these vectors represent.

field name: Literal['tags_index'] = 'tags_index'
field target: VectorData | None = None

Reference to the target dataset that this index applies to.

linkml_meta: ClassVar[LinkML_Meta] = FieldInfo(annotation=NoneType, required=False, default=LinkML_Meta(tree_root=False), frozen=True)
pydantic model TimeIntervalsTimeseriesIndex

Bases: VectorIndex

Index for timeseries.

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

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

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

Config:

  • validate_assignment: bool = True

  • validate_default: bool = True

  • extra: str = forbid

  • arbitrary_types_allowed: bool = True

  • use_enum_values: bool = True

Fields:
field array: NDArray[Shape['* dim0'], Any] | NDArray[Shape['* dim0, * dim1'], Any] | NDArray[Shape['* dim0, * dim1, * dim2'], Any] | NDArray[Shape['* dim0, * dim1, * dim2, * dim3'], Any] | None = None
field description: str | None = None

Description of what these vectors represent.

field name: Literal['timeseries_index'] = 'timeseries_index'
field target: VectorData | None = None

Reference to the target dataset that this index applies to.

linkml_meta: ClassVar[LinkML_Meta] = FieldInfo(annotation=NoneType, required=False, default=LinkML_Meta(tree_root=False), frozen=True)