def resample_time(trj: TrajaDataFrame, step_time: str, new_fps: bool = None):
"""Returns a ``TrajaDataFrame`` resampled to consistent `step_time` intervals.
Args:
trj (:class:`~traja.frame.TrajaDataFrame`): Trajectory
step_time (str): step time interval (eg, '1s')
new_fps (bool, optional): new fps
Results:
trj (:class:`~traja.frame.TrajaDataFrame`): Trajectory
.. doctest::
>>> from traja import generate
>>> from traja.trajectory import resample_time
>>> df = generate()
>>> resampled = resample_time(df, '2s')
>>> resampled.head()
time x y
0 00:00:00 14.555071 -26.482614
1 00:00:02 -3.582797 -6.491297
2 00:00:04 -4.299709 26.937443
3 00:00:06 -25.337042 42.131848
4 00:00:08 33.069915 32.780830
"""
time_col = _get_time_col(trj)
if time_col is "index" and is_datetime64_any_dtype(trj.index):
_trj = _resample_time(trj, step_time)
elif time_col is "index" and is_timedelta64_dtype(trj.index):
_trj = _resample_time(trj, step_time)
elif time_col:
if isinstance(step_time, str):
try:
if "." in step_time:
raise NotImplementedError("Fractional step time not implemented.")
except Exception:
raise NotImplementedError(
f"Inferring from time format {step_time} not yet implemented."
)
_trj = trj.set_index(time_col)
_trj.index = pd.to_timedelta(_trj.index, unit="s")
_trj = _resample_time(_trj, step_time)
_trj.reset_index(inplace=True)
else:
raise NotImplementedError(
f"Time column ({time_col}) not of expected data type."
)
return _trj
def resample_time(trj: TrajaDataFrame,
step_time: str,
new_fps: Optional[bool] = None):
"""Returns a ``TrajaDataFrame`` resampled to consistent `step_time` intervals.
``step_time`` should be expressed as a number-time unit combination, eg "2S" for 2 seconds and “2100L” for 2100 milliseconds.
Args:
trj (:class:`~traja.frame.TrajaDataFrame`): Trajectory
step_time (str): step time interval / offset string (eg, '2S' (seconds), '50L' (milliseconds), '50N' (nanoseconds))
new_fps (bool, optional): new fps
Results:
trj (:class:`~traja.frame.TrajaDataFrame`): Trajectory
.. doctest::
>>> from traja import generate, resample_time
>>> df = generate()
>>> resampled = resample_time(df, '50L') # 50 milliseconds
>>> resampled.head()
x y
time
1970-01-01 00:00:00.000 0.000000 0.000000
1970-01-01 00:00:00.050 0.999571 4.293384
1970-01-01 00:00:00.100 -1.298510 5.423373
1970-01-01 00:00:00.150 -6.056916 4.874502
1970-01-01 00:00:00.200 -10.347759 2.108385
"""
time_col = _get_time_col(trj)
if time_col == "index" and is_datetime64_any_dtype(trj.index):
_trj = _resample_time(trj, step_time)
elif time_col == "index" and is_timedelta64_dtype(trj.index):
trj.index = pd.to_datetime(trj.index)
_trj = _resample_time(trj, step_time)
_trj.index = pd.to_timedelta(_trj.index)
elif time_col:
if isinstance(step_time, str):
try:
if "." in step_time:
raise NotImplementedError(
"""Fractional step time not implemented.
For milliseconds/microseconds/nanoseconds use:
L milliseonds
U microseconds
N nanoseconds
eg, step_time='2100L'""")
except Exception:
raise NotImplementedError(
f"Inferring from time format {step_time} not yet implemented."
)
_trj = trj.set_index(time_col)
time_units = _trj.__dict__.get("time_units", "s")
_trj.index = pd.to_datetime(_trj.index, unit=time_units)
_trj = _resample_time(_trj, step_time)
else:
raise NotImplementedError(
f"Time column ({time_col}) not of expected datasets type.")
return _trj