to_dlc_style_df#

movement.io.save_poses.to_dlc_style_df(ds, split_individuals=False)[source]#

Convert a movement dataset to DeepLabCut-style DataFrame(s).

Parameters:

ds (xarray.Dataset) – movement dataset containing pose tracks, confidence scores, and associated metadata.
split_individuals (bool, optional) – If True, return a dictionary of DataFrames per individual, with individual names as keys. If False (default), return a single DataFrame for all individuals (see Notes).

Returns:

DeepLabCut-style pandas DataFrame or dictionary of DataFrames.

Return type:

pandas.DataFrame or dict

Notes

The DataFrame(s) will have a multi-index column with the following levels: “scorer”, “bodyparts”, “coords” (if split_individuals is True), or “scorer”, “individuals”, “bodyparts”, “coords” (if split_individuals is False).

Regardless of the provenance of the points-wise confidence scores, they will be referred to as “likelihood”, and stored in the “coords” level (as DeepLabCut expects).