BIDS Models#

class BidsSessionMetadata(

*,

session_id: str | None = None,

participant: Participant,

general_metadata: GeneralMetadata,

events: Events | None = None,

probe_table: ProbeTable | None = None,

electrode_table: ElectrodeTable | None = None,

channel_table: ChannelTable | None = None,

has_units_table: bool = False,

has_electrical_series_in_acquisition: bool = False,

run_config: RunConfig = <factory>,

sanitization: Sanitization | None = None,

**extra_data: Any,

)[source]#

Bases: BaseMetadataContainerModel

Schema for the metadata of a single BIDS session.

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.

session_id: str | None#

participant: Participant#

general_metadata: GeneralMetadata#

events: Events | None#

probe_table: ProbeTable | None#

electrode_table: ElectrodeTable | None#

channel_table: ChannelTable | None#

has_units_table: bool#

has_electrical_series_in_acquisition: bool#

run_config: RunConfig#

sanitization: Sanitization | None#

model_post_init(context: Any, /) → None[source]#

This function is meant to behave like a BaseModel method to initialize private attributes.

It takes context as an argument since that’s what pydantic-core passes when calling it.

Args:: self: The BaseModel instance. context: The context.

property notifications: list[Notification]#

All notifications from contained session converters.

These can accumulate over time based on which instance methods have been called.

classmethod from_nwbfile_paths( nwbfile_paths: list[Annotated[Path, PathType(path_type=file)]] | list[HttpUrl] = FieldInfo(annotation=NoneType, required=True, metadata=[MinLen(min_length=1)]), run_config: RunConfig = FieldInfo(annotation=NoneType, required=False, default_factory=RunConfig), ) → Self[source]#

model_config = {'extra': 'allow', 'validate_assignment': True}#: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class Channel(

*,

notifications: list[Notification] = <factory>,

name: str,

electrode_name: str,

type: str,

units: str,

sampling_frequency: float,

low_cutoff: float | None = None,

high_cutoff: float | None = None,

reference: str | None = None,

notch: str | None = None,

channel_label: str | None = None,

stream_id: str | None = None,

description: str | None = None,

software_filter_types: str | None = None,

status: Literal['good',

'bad',

'n/a'] | None=None,

status_description: str | None = None,

gain: float | None = None,

time_offset: float | None = None,

time_reference_channel: str | None = None,

ground: str | None = None,

recording_mode: str | None = None,

**extra_data: Any,

)[source]#

Bases: BaseMetadataModel

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.

name: str#

electrode_name: str#

type: str#

units: str#

sampling_frequency: float#

low_cutoff: float | None#

high_cutoff: float | None#

reference: str | None#

notch: str | None#

channel_label: str | None#

stream_id: str | None#

description: str | None#

software_filter_types: str | None#

status: Literal['good', 'bad', 'n/a'] | None#

status_description: str | None#

gain: float | None#

time_offset: float | None#

time_reference_channel: str | None#

ground: str | None#

recording_mode: str | None#

model_config = {'extra': 'allow', 'validate_assignment': True}#: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class ChannelTable(

*,

channels: list[Channel],

modality: Literal['ecephys', 'icephys'],

**extra_data: Any,

)[source]#

Bases: BaseMetadataContainerModel

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.

channels: list[Channel]#

modality: Literal['ecephys', 'icephys']#

property notifications: list[Notification]#

All notifications from contained session converters.

These can accumulate over time based on which instance methods have been called.

classmethod from_nwbfiles( nwbfiles: list[Annotated[NWBFile, InstanceOf()]], ) → Self | None[source]#

to_tsv(file_path: str | Path)[source]#

Write the channels data to a TSV file.

Parameters:: file_path (path) – The path where the TSV file will be saved.

to_json(file_path: str | Path) → None[source]#

Save the channels information to a JSON file.

Parameters:: file_path (path) – The path to the output JSON file.

model_config = {'extra': 'allow', 'validate_assignment': True}#: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_post_init(context: Any, /) → None#

This function is meant to behave like a BaseModel method to initialize private attributes.

It takes context as an argument since that’s what pydantic-core passes when calling it.

Args:: self: The BaseModel instance. context: The context.

class DatasetDescription(*, notifications: list[~nwb2bids.notifications._notification.Notification] = <factory>, Name: str | None = None, BIDSVersion: ~typing.Annotated[str | None, _PydanticGeneralMetadata(pattern='^\\d+\\.\\d+(?:\\.\\d+)?$')], HEDVersion: ~typing.Annotated[str | None, _PydanticGeneralMetadata(pattern='^\\d+\\.\\d+(?:\\.\\d+)?$')], Description: str | None = None, DatasetType: ~typing.Literal['raw', 'derivative'] = 'raw', Authors: list[str] | None = None, License: ~typing.Literal['CC-BY-4.0', 'CC0-1.0'] | None = None, GeneratedBy: list[~nwb2bids.bids_models._dataset_description.GeneratedByItem] | None = None, **extra_data: ~typing.Any)[source]#

Bases: BaseMetadataModel

Schema for the dataset description in BIDS format.

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.

Name: str | None#

BIDSVersion: str | None#

HEDVersion: str | None#

Description: str | None#

DatasetType: Literal['raw', 'derivative']#

Authors: list[str] | None#

License: Literal['CC-BY-4.0', 'CC0-1.0'] | None#

GeneratedBy: list[GeneratedByItem] | None#

model_post_init(context: Any, /) → None[source]#: Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.

validate_exactly_one_nwb2bids() → Self[source]#

classmethod from_file_path( file_path: Annotated[Path, PathType(path_type=file)], ) → Self | None[source]#

Load the BIDS dataset description from a JSON file.

Parameters:: file_path (FilePath) – Path to the JSON file containing the dataset metadata.
Returns:: An instance of DatasetDescription populated with data from the file.
Return type:: BidsDatasetMetadata or None

model_config = {'extra': 'allow', 'validate_assignment': True}#: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class Electrode(

*,

notifications: list[Notification] = <factory>,

name: str,

probe_name: str,

x: float = nan,

y: float = nan,

z: float = nan,

hemisphere: Literal['L',

'R',

'n/a']='n/a',

impedance: float = nan,

shank_id: str = 'n/a',

size: float | None = None,

electrode_shape: str | None = None,

material: str | None = None,

location: str | None = None,

pipette_solution: str | None = None,

internal_pipette_diameter: float | None = None,

external_pipette_diameter: float | None = None,

**extra_data: Any,

)[source]#

Bases: BaseMetadataModel

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.

name: str#

probe_name: str#

x: float#

y: float#

z: float#

hemisphere: Literal['L', 'R', 'n/a']#

impedance: float#

shank_id: str#

size: float | None#

electrode_shape: str | None#

material: str | None#

location: str | None#

pipette_solution: str | None#

internal_pipette_diameter: float | None#

external_pipette_diameter: float | None#

model_config = {'extra': 'allow', 'validate_assignment': True}#: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class ElectrodeTable(

*,

electrodes: list[Electrode],

modality: Literal['ecephys', 'icephys'],

**extra_data: Any,

)[source]#

Bases: BaseMetadataContainerModel

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.

electrodes: list[Electrode]#

modality: Literal['ecephys', 'icephys']#

property notifications: list[Notification]#

All notifications from contained session converters.

These can accumulate over time based on which instance methods have been called.

classmethod from_nwbfiles( nwbfiles: list[Annotated[NWBFile, InstanceOf()]], ) → Self | None[source]#

to_tsv(file_path: str | Path) → None[source]#

Write the electrode data to a TSV file.

Parameters:: file_path (path) – The path to the output TSV file.

to_json(file_path: str | Path) → None[source]#

Save the electrode information to a JSON file.

Parameters:: file_path (path) – The path to the output JSON file.

model_config = {'extra': 'allow', 'validate_assignment': True}#: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_post_init(context: Any, /) → None#

This function is meant to behave like a BaseModel method to initialize private attributes.

It takes context as an argument since that’s what pydantic-core passes when calling it.

Args:: self: The BaseModel instance. context: The context.

Bases: BaseModel

General device and session metadata extracted from NWB files.

While NWB treats this information as high-level session-specific metadata, BIDS treats these fields as modality specific and as pertaining to ‘parameters’ that can vary.

This should typically be written to two files, depending on the modality:

_ecephys.json
_icephys.json

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.

InstitutionName: str | None#

InstitutionAddress: str | None#

InstitutionalDepartmentName: str | None#

PowerLineFrequency: float | Literal['n/a']#

Manufacturer: str | None#

ManufacturersModelName: str | None#

ManufacturersModelVersion: str | None#

RecordingSetupName: str | None#

SamplingFrequency: float#

DeviceSerialNumber: str | None#

SoftwareName: str | None#

SoftwareVersions: str | None#

RecordingDuration: float | None#

RecordingType: str | None#

EpochLength: float | None#

SoftwareFilters: dict[str, dict[str, Any]] | Literal['n/a']#

HardwareFilters: dict[str, dict[str, Any]] | Literal['n/a']#

PharmaceuticalName: str | None#

PharmaceuticalDoseAmount: float | list[float] | None#

PharmaceuticalDoseUnits: str | None#

PharmaceuticalDoseRegimen: str | None#

PharmaceuticalDoseTime: float | list[float] | None#

BodyPart: str | None#

BodyPartDetails: str | None#

BodyPartDetailsOntology: str | None#

SampleEnvironment: str | None#

SampleEmbedding: str | None#

SliceThickness: int | float | None#

SampleExtractionProtocol: str | None#

SupplementarySignals: str | None#

TaskName: str | None#

TaskDescription: str | None#

Instructions: str | None#

CogAtlasID: str | None#

CogPOID: str | None#

model_config = {'extra': 'allow', 'validate_assignment': True}#: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod from_nwbfiles( nwbfiles: list[Annotated[NWBFile, InstanceOf()]], ) → Self[source]#: Extracts all unique general metadata from the in-memory NWBFile objects.

to_json(file_path: str | Path) → None[source]#

Save the general metadata to a JSON file.

Parameters:: file_path (str or pathlib.Path) – The path to the file where the metadata will be saved.

class Participant(

*,

notifications: list[Notification] = <factory>,

participant_id: str | None = None,

species: str | None = None,

sex: str | None = None,

strain: str | None = None,

**extra_data: Any,

)[source]#

Bases: BaseMetadataModel

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.

participant_id: str | None#

species: str | None#

sex: str | None#

strain: str | None#

classmethod from_nwbfiles( nwbfiles: list[Annotated[NWBFile, InstanceOf()]], ) → Self[source]#: Extracts participant metadata from the in-memory NWBFile objects.

model_config = {'extra': 'allow', 'validate_assignment': True}#: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

write_coordsystem_json( file_path: str | Path, space: Literal['AllenCCFv3', 'PaxinosWatson'], ) → None[source]#

Write a BIDS coordinate system JSON sidecar file for the given space label.

Parameters:

file_path (path) – The path to the output *_coordsystem.json file.
space ({“AllenCCFv3”, “PaxinosWatson”}) – The space/atlas label.