neuralib.tracking.deeplabcut.core.DeepLabCutResult

class neuralib.tracking.deeplabcut.core.DeepLabCutResult[source]

Bases: object

__init__(dat, meta, filtered, time=None)[source]
Parameters:

  • dat (DataFrame) – Deeplabcut results as polars dataframe

  • meta (DeepLabCutMeta) – Deeplabcut meta typeddict

  • filtered (bool) – If the Deeplabcut results is filtered or not

  • time (ndarray | None) – 1D time array for each tracked frames. If None, then assume stable DAQ and calculated from meta.

property is_filtered: bool
property meta: DeepLabCutMeta
property joints: list[str]

list of labelled joints

property fps: float
property nframes: int
property time: ndarray
with_global_lh_filter(lh)[source]

With global likelihood filter :param lh: likelihood threshold :return: DeepLabCutResult

Parameters:

lh (float)

Return type:

Self