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[trackingdata] add fps, some docs, change interpolate

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Jan Grewe 2022-09-12 16:56:43 +02:00
parent 6f9633a74e
commit 3e1cbe4b9b
1 changed files with 20 additions and 13 deletions
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33
etrack/tracking_data.py
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@ -23,6 +23,7 @@ class TrackingData(object):
self._threshold = quality_threshold self._threshold = quality_threshold
self._position_limits = position_limits self._position_limits = position_limits
self._time_limits = temporal_limits self._time_limits = temporal_limits
self._fps = fps
@property @property
def original_positions(self): def original_positions(self):
@ -32,16 +33,17 @@ class TrackingData(object):
def original_quality(self): def original_quality(self):
return self._orgquality return self._orgquality
def interpolate(self, store=True, min_count=10): def interpolate(self, start_time=None, end_time=None, min_count=5):
if len(self._x) < min_count: if len(self._x) < min_count:
print(f"{self._node} data has less than {min_count} data points with sufficient quality!") print(f"{self._node} data has less than {min_count} data points with sufficient quality ({len(self._x)})!")
return None return None, None, None
x = np.interp(self._orgtime, self._time, self._x) start = self._time[0] if start_time is None else start_time
y = np.interp(self._orgtime, self._time, self._y) end = self._time[-1] if end_time is None else end_time
if store: time = np.arange(start, end, 1./self._fps)
self._x = x x = np.interp(time, self._time, self._x)
self._y = y y = np.interp(time, self._time, self._y)
self._time = self._orgtime.copy()
return x, y, time
@property @property
def quality_threshold(self): def quality_threshold(self):
@ -96,9 +98,14 @@ class TrackingData(object):
raise ValueError(f"The new_limits vector must be a 2-tuple of the form (start, end). ") raise ValueError(f"The new_limits vector must be a 2-tuple of the form (start, end). ")
self._time_limits = new_limits self._time_limits = new_limits
def filter_tracks(self): def filter_tracks(self, align_time=True):
"""Applies the filters to the tracking data. All filters will be applied squentially, i.e. an AND connection. """Applies the filters to the tracking data. All filters will be applied sequentially, i.e. an AND connection.
To change the filter settings use the setters for 'quality_threshold', 'temporal_limits', 'position_limits'. Setting them to None disables the respective filter discarding the setting. To change the filter settings use the setters for 'quality_threshold', 'temporal_limits', 'position_limits'. Setting them to None disables the respective filter discarding the setting.
Parameters
----------
align_time: bool
Controls whether the time vector is aligned to the first time point at which the agent is within the positional_limits. Default = True
""" """
self._x = self._orgx.copy() self._x = self._orgx.copy()
self._y = self._orgy.copy() self._y = self._orgy.copy()
@ -112,9 +119,9 @@ class TrackingData(object):
(self._y >= self.position_limits[1]) & (self._y < y_max)) (self._y >= self.position_limits[1]) & (self._y < y_max))
self._x = self._x[indices] self._x = self._x[indices]
self._y = self._y[indices] self._y = self._y[indices]
self._time = self._time[indices] self._time = self._time[indices] - self._time[0] if align_time else 0.0
self._quality = self._quality[indices] self._quality = self._quality[indices]
if self.temporal_limits is not None: if self.temporal_limits is not None:
indices = np.where((self._time >= self.temporal_limits[0]) & indices = np.where((self._time >= self.temporal_limits[0]) &
(self._time < self.temporal_limits[1])) (self._time < self.temporal_limits[1]))