ParticleDetection.reconstruct_3D.tracking

Collection of previously used automatic rod tracking approaches. These are just implemented for comparison with new, more promising methods.

Authors: Dmitry Puzyrev (dmitry.puzyrev@ovgu.de), Adrian Niemann (adrian.niemann@ovgu.de)

Date: 31.10.2022

tracking_global_assignment(data: DataFrame) → Tuple[DataFrame, ndarray]

Tracks rods (one colour) over multiple frames with optimal assignment.

The rods given are matched with all others in the next frame and the optimal assignment is determined by comparing the distances between the endpoints.

Parameters:

data (DataFrame) – Data(-slice) from rod tracking. Must contain at least the following columns: x1, y1, z1, x2, y2, z2, frame, particle(, unseen)

Returns:

Tuple[DataFrame, ndarray] – Retuns the tracked data, i.e. the initial data with adjusted particle numbers. Additionlly, returns the assignment costs per frame, i.e. the distance between the endpoints of all matched rods.

tracking_trackpy(data: DataFrame, report: bool = False) → DataFrame

Tracks rods (one colour) over multiple frames using trackpy.

Parameters:

• data (pd.DataFrame) – _Data(-slice) from rod tracking. Must contain at least the following columns: x, y, z,

• report (bool, optional) – Flag, whether to print the number of rods before and after tracking. By default False.

Returns:

pd.DataFrame