openlifu.db.session.Session

class openlifu.db.session.Session(id: ~typing.Annotated[str | None, OpenLIFUFieldData(name='Session ID', description='ID of this session')] = None, subject_id: ~typing.Annotated[str | None, OpenLIFUFieldData(name='Subject ID', description='ID of the parent subject of this session')] = None, name: ~typing.Annotated[str | None, OpenLIFUFieldData(name='Session name', description='Session name')] = None, date_created: ~typing.Annotated[~datetime.datetime, OpenLIFUFieldData(name='Date created', description='Date of creation of the session')] = <factory>, date_modified: ~typing.Annotated[~datetime.datetime, OpenLIFUFieldData(name='Date modified', description='Date of modification of the session')] = <factory>, protocol_id: ~typing.Annotated[str | None, OpenLIFUFieldData(name='Protocol ID', description='ID of the protocol used for this session')] = None, volume_id: ~typing.Annotated[str | None, OpenLIFUFieldData(name='Volume ID', description='ID of the subject volume associated with this session')] = None, transducer_id: ~typing.Annotated[str | None, OpenLIFUFieldData(name='Transducer ID', description='ID of the transducer associated with this session')] = None, array_transform: ~typing.Annotated[~openlifu.geo.ArrayTransform, OpenLIFUFieldData(name='Array transform', description='The transducer affine transform matrix with units, situating the transducer in space')] = <factory>, targets: ~typing.Annotated[~typing.List[~openlifu.geo.Point], OpenLIFUFieldData(name='Targets', description='Targets saved to this session')] = <factory>, markers: ~typing.Annotated[~typing.List[~openlifu.geo.Point], OpenLIFUFieldData(name='Markers', description='Registration markers saved to this session')] = <factory>, attrs: ~typing.Annotated[dict, OpenLIFUFieldData(name='Custom attributes', description='Dictionary of additional custom attributes to save to the session')] = <factory>, virtual_fit_results: ~typing.Annotated[~typing.Dict[str, ~typing.List[~typing.Tuple[bool, ~openlifu.geo.ArrayTransform]]], OpenLIFUFieldData(name='Virtual fit results', description='Virtual fit results. This is a dictionary mapping target IDs to a list of (approval, transform) pairs')] = <factory>, transducer_tracking_results: ~typing.Annotated[~typing.List[~openlifu.db.session.TransducerTrackingResult], OpenLIFUFieldData(name='Tracking results', description='List of any transducer tracking results')] = <factory>)

Bases: object

Class representing an openlifu session, which consists essentially of a patient scan, a protocol to use, potential targets for sonication, and a transducer situated in the patient space.

array_transform: Annotated[ArrayTransform, OpenLIFUFieldData(name='Array transform', description='The transducer affine transform matrix with units, situating the transducer in space')]

The transducer affine transform matrix with units, situating the transducer in space

attrs: Annotated[dict, OpenLIFUFieldData(name='Custom attributes', description='Dictionary of additional custom attributes to save to the session')]

Dictionary of additional custom attributes to save to the session

date_created: Annotated[datetime, OpenLIFUFieldData(name='Date created', description='Date of creation of the session')]

Date of creation of the session

date_modified: Annotated[datetime, OpenLIFUFieldData(name='Date modified', description='Date of modification of the session')]

Date of modification of the session

static from_dict(d: Dict)

Create a session from a dictionary

Parameters:

d – Dictionary of session parameters

Returns:

Session object

static from_file(filename)

Create a Session from a file

Parameters:

filename – Name of the file to read

Returns:

Session object

static from_json(json_string: str) → Session

Load a Session from a json string

id: Annotated[str | None, OpenLIFUFieldData(name='Session ID', description='ID of this session')] = None

ID of this session

markers: Annotated[List[Point], OpenLIFUFieldData(name='Markers', description='Registration markers saved to this session')]

Registration markers saved to this session

name: Annotated[str | None, OpenLIFUFieldData(name='Session name', description='Session name')] = None

Session name

protocol_id: Annotated[str | None, OpenLIFUFieldData(name='Protocol ID', description='ID of the protocol used for this session')] = None

ID of the protocol used for this session

subject_id: Annotated[str | None, OpenLIFUFieldData(name='Subject ID', description='ID of the parent subject of this session')] = None

ID of the parent subject of this session

targets: Annotated[List[Point], OpenLIFUFieldData(name='Targets', description='Targets saved to this session')]

Targets saved to this session

to_dict()

Convert the session to a dictionary

Returns:

Dictionary of session parameters

to_file(filename)

Save the session to a file

Parameters:

filename – Name of the file

to_json(compact: bool) → str

Serialize a Session to a json string

Parameters:

compact – if enabled then the string is compact (not pretty). Disable for pretty.

Returns: A json string representing the complete Session object.

transducer_id: Annotated[str | None, OpenLIFUFieldData(name='Transducer ID', description='ID of the transducer associated with this session')] = None

ID of the transducer associated with this session

transducer_tracking_results: Annotated[List[TransducerTrackingResult], OpenLIFUFieldData(name='Tracking results', description='List of any transducer tracking results')]

List of any transducer tracking results

virtual_fit_results: Annotated[Dict[str, List[Tuple[bool, ArrayTransform]]], OpenLIFUFieldData(name='Virtual fit results', description='Virtual fit results. This is a dictionary mapping target IDs to a list of (approval, transform) pairs')]

Virtual fit results. This is a dictionary mapping target IDs to a list of (approval, transform) pairs, where:

approval is a boolean indicating whether the specific virtual fit transform has been approved for sonication, and transform is a transducer transform generated by the virtual fit for that target.

The idea is that the list of transforms would be ordered from best to worst, and should of course contain at least one transform. The “approval” associated with each transform indicates whether the transform has been approved for sonication.

volume_id: Annotated[str | None, OpenLIFUFieldData(name='Volume ID', description='ID of the subject volume associated with this session')] = None

ID of the subject volume associated with this session