neuralset.events.study.StudyInfo

class neuralset.events.study.StudyInfo(*, num_timelines: int = 0, num_subjects: int = 0, query: str = 'timeline_index < 1', num_events_in_query: int = 0, event_types_in_query: set[str] = {}, data_shape: tuple[int, ...] = (), frequency: float = 0.0, fmri_spaces: tuple[str, ...] | set[str] = ())[source][source]

Records expected dataset characteristics for testing and validation.

Provides a baseline for automatic unit tests to verify that a study’s data loading logic and file parsing behave correctly and completely.

num_timelines[source]

The total number of timelines (e.g. subject sessions) expected.

Type:

int

num_subjects[source]

The expected number of unique subjects.

Type:

int

query[source]

A query applied during tests to subsample the data (default: "timeline_index < 1").

Type:

str

num_events_in_query[source]

The expected number of events after applying the query.

Type:

int

event_types_in_query[source]

The expected set of event types present in the queried data.

Type:

set of str

data_shape[source]

The expected shape of the primary data arrays.

Type:

tuple of int

frequency[source]

The expected sampling frequency of the data, in Hz.

Type:

float

fmri_spaces[source]

(fMRI only) The expected spatial reference spaces for the data.

Type:

tuple of str