def rediscretize_points(trj: TrajaDataFrame,
R: Union[float, int],
time_out=False):
"""Returns a ``TrajaDataFrame`` rediscretized to a constant step length `R`.
Args:
trj (:class:`traja.frame.TrajaDataFrame`): Trajectory
R (float): Rediscretized step length (eg, 0.02)
time_out (bool): Include time corresponding to time intervals in output
Returns:
rt (:class:`numpy.ndarray`): rediscretized trajectory
"""
if not isinstance(R, (float, int)):
raise TypeError(f"R should be float or int, but is {type(R)}")
results = _rediscretize_points(trj, R, time_out)
rt = results["rt"]
if len(rt) < 2:
raise RuntimeError(
f"Step length {R} is too large for path (path length {len(trj)})")
rt = traja.from_xy(rt)
if time_out:
rt["time"] = results["time"]
return rt
def plot_xy(xy: np.ndarray, *args: Optional, **kwargs: Optional):
"""Plot trajectory from xy values.
Args:
xy (np.ndarray) : xy values of dimensions N x 2
*args : Plot args
**kwargs : Plot kwargs
"""
trj = traja.from_xy(xy)
trj.traja.plot(*args, **kwargs)
def rediscretize_points(trj: TrajaDataFrame, R: Union[float, int]):
"""Returns a ``TrajaDataFrame`` rediscretized to a constant step length `R`.
Args:
trj (:class:`traja.frame.TrajaDataFrame`): Trajectory
R (float): Rediscretized step length (eg, 0.02)
Returns:
rt (:class:`numpy.ndarray`): rediscretized trajectory
"""
rt = _rediscretize_points(trj, R)
if len(rt) < 2:
raise RuntimeError(
f"Step length {R} is too large for path (path length {len(self._trj)})"
)
rt = traja.from_xy(rt)
return rt
def traj_from_coords(
track: Union[np.ndarray, pd.DataFrame],
x_col=1,
y_col=2,
time_col: Optional[str] = None,
fps: Union[float, int] = 4,
spatial_units: str = "m",
time_units: str = "s",
) -> TrajaDataFrame:
"""Create TrajaDataFrame from coordinates.
Args:
track: N x 2 numpy array or pandas DataFrame with x and y columns
x_col: column index or x column name
y_col: column index or y column name
time_col: name of time column
fps: Frames per seconds
spatial_units: default m, optional
time_units: default s, optional
Returns:
trj: TrajaDataFrame
.. doctest::
>> xy = np.random.random((1000, 2))
>> trj = traja.traj_from_coord(xy)
>> assert trj.shape == (1000,4) # columns x, y, time, dt
"""
if not isinstance(track, traja.TrajaDataFrame):
if isinstance(track, np.ndarray) and track.shape[1] == 2:
trj = traja.from_xy(track)
elif isinstance(track, pd.DataFrame):
trj = traja.TrajaDataFrame(track)
else:
trj = track
trj.traja.spatial_units = spatial_units
trj.traja.time_units = time_units
def rename(col, name, trj):
if isinstance(col, int):
trj.rename(columns={col: name})
else:
if col not in trj:
raise Exception(f"Missing column {col}")
trj.rename(columns={col: name})
return trj
# Ensure column names are as expected
trj = rename(x_col, "x", trj)
trj = rename(y_col, "y", trj)
if time_col is not None:
trj = rename(time_col, "time", trj)
# Allocate times if they aren't already known
if "time" not in trj:
if fps is None:
raise Exception((
"Cannot create a trajectory without times: either fps or a time column must be specified"
))
# Assign times to each frame, starting at 0
trj["time"] = pd.Series(np.arange(0, len(trj)) / fps)
# Get displacement time for each coordinate, with the first point at time 0
trj["dt"] = trj.time - trj.time.iloc[0]
return trj
def test_from_xy():
df_copy = df.copy()
expected = traja.from_xy(df_copy.traja.xy).values
actual = df_copy.traja.xy
npt.assert_allclose(expected, actual)
