import matplotlib.pyplot as plt import pandas as pd import numpy as np import numbers as nb import os class TrackingResult(): def __init__(self, results_file) -> None: super().__init__() if not os.path.exists(results_file): raise ValueError("File %s does not exist!" % results_file) self._file_name = results_file self._data_frame = pd.read_hdf(results_file) self._level_shape = self._data_frame.columns.levshape self._scorer = self._data_frame.columns.levels[0].values self._bodyparts = self._data_frame.columns.levels[1].values if self._level_shape[1] > 0 else [] self._positions = self._data_frame.columns.levels[2].values if self._level_shape[2] > 0 else [] @property def filename(self): return self._file_name @property def dataframe(self): return self._data_frame @property def scorer(self): return self._scorer @property def bodyparts(self): return self._bodyparts @property def positions(self): return self._positions def position_values(self, scorer=0, bodypart=0, framerate=30): if isinstance(scorer, nb.Number): sc = self._scorer[scorer] elif isinstance(scorer, str) and scorer in self._scorer: sc = scorer else: raise ValueError("Scorer %s is not in dataframe!" % scorer) if isinstance(bodypart, nb.Number): bp = self._bodyparts[bodypart] elif isinstance(bodypart, str) and bodypart in self._bodyparts: bp = bodypart else: raise ValueError("Bodypart %s is not in dataframe!" % bodypart) x = self._data_frame[sc][bp]["x"] if "x" in self._positions else [] y = self._data_frame[sc][bp]["y"] if "y" in self._positions else [] l = self._data_frame[sc][bp]["likelihood"] if "likelihood" in self._positions else [] time = np.arange(len(self._data_frame))/framerate return time, x, y, l, bp def plot(self, scorer=0, bodypart=0, threshold=0.9, framerate=30): t, x, y, l, name = self.position_values(scorer=scorer, bodypart=bodypart, framerate=framerate) plt.scatter(x[l > threshold], y[l > threshold], c=t[l > threshold], label=name) plt.plot(x[l > threshold], y[l > threshold]) plt.xlabel("x position") plt.ylabel("y position") plt.gca().invert_yaxis() bar = plt.colorbar() bar.set_label("time [s]") plt.legend() plt.show()