treadmill

Treadmill loader.

Data is reconstructed entirely from the central *_dataqueue.csv log: each EncoderData(timestamp=..., distance=..., speed=...) payload row carries the full sample, already published on the master clock via queue_elapsed. The per-session *_treadmill.csv is only consulted as a fallback when no dataqueue is available for that session (e.g. legacy fixtures used by the treadmill_csv_fallback test).

class mesofield.datakit.sources.behavior.treadmill.TreadmillSource

Bases: TimeseriesSource

Load treadmill samples aligned to the experiment window.

requires: ClassVar[Tuple[str, ...]] = ('dataqueue',)

Tag names of upstream sources whose loaded streams should be made available via LoadContext.dependencies. Soft contract: a missing or failed dependency yields None in dependencies[tag]; sources are responsible for either degrading gracefully or raising.

build_timeseries(path, *, context=None)

Return (timeline, value, meta).

Parameters:

• path (Path)

• context (LoadContext | None)

Return type:

tuple[ndarray, DataFrame, dict]