Source code for ddd_pylib.tracking._trackpy_strategy

from ._base_tracking_strategy import BaseTrackingStrategy
import trackpy as tp
import pandas as pd




class TrackpyStrategy(BaseTrackingStrategy):
    def __init__(self):
        super().__init__()
        tp.quiet(True)
        self._adaptiveStop = 0.01
        self._adaptiveStep = 0.75



    def getAdaptiveStop(self) -> float:
        return self._adaptiveStop




    def setAdaptiveStop(self, stop: float):
        if stop <= 0:
            raise ValueError("Adaptive stop must be positive.")
        self._adaptiveStop = stop




    def getAdaptiveStep(self) -> float:
        return self._adaptiveStep




    def setAdaptiveStep(self, step: float):
        if step <= 0 or step >= 1:
            raise ValueError("Adaptive step must be between 0 and 1.")
        self._adaptiveStep = step


    def _linkTracks(self) -> pd.DataFrame:
        d = self.getDetections()
        predictor = tp.predict.NearestVelocityPredict()
        pos_columns = [a for a in ['Z', 'Y', 'X'] if a in d.columns]
        
        linked = predictor.link_df(
            d,
            search_range=self._searchingDistance,
            memory=self._getUncalibratedMemory(),
            pos_columns=pos_columns,
            t_column='T',
            adaptive_stop=self._adaptiveStop,
            adaptive_step=self._adaptiveStep
        )
        d["track_id"] = linked["particle"].astype(int) + 1
        return d