def _interp_time_orientation(self, time: Time) -> xr.DataArray:
"""Interpolate the orientation in time."""
if "time" not in self.orientation.dims: # don't interpolate static
return self.orientation
if time.max() <= self.time.min(): # only use edge timestamp
return self.orientation.isel(time=0).data
if time.min() >= self.time.max(): # only use edge timestamp
return self.orientation.isel(time=-1).data
# full interpolation with overlapping times
return ut.xr_interp_orientation_in_time(self.orientation, time)
def xr_interp_orientation_in_time(da: xr.DataArray,
time: types_time_like) -> xr.DataArray:
"""Interpolate an xarray DataArray that represents orientation data in time.
Parameters
----------
da :
xarray DataArray containing the orientation as matrix
time :
Time data
Returns
-------
xarray.DataArray
Interpolated data
"""
if "time" not in da.dims:
return da
if len(da.time) == 1: # remove "time dimension" for static case
return da.isel({"time": 0})
time = Time(time).as_pandas_index()
time_da = Time(da).as_pandas_index()
time_ref = da.weldx.time_ref
if not len(time_da) > 1:
raise ValueError("Invalid time format for interpolation.")
# extract intersecting times and add time range boundaries of the data set
times_ds_limits = pd.Index([time_da.min(), time_da.max()])
times_union = time.union(times_ds_limits)
times_intersect = times_union[(times_union >= times_ds_limits[0])
& (times_union <= times_ds_limits[1])]
# interpolate rotations in the intersecting time range
rotations_key = Rot.from_matrix(da.transpose(..., "time", "c", "v").data)
times_key = time_da.view(np.int64)
rotations_interp = Slerp(times_key,
rotations_key)(times_intersect.view(np.int64))
da = xr_3d_matrix(rotations_interp.as_matrix(), times_intersect)
# use interp_like to select original time values and correctly fill time dimension
da = xr_interp_like(da, {"time": time}, fillna=True)
# resync and reset to correct format
if time_ref:
da.weldx.time_ref = time_ref
da = da.weldx.time_ref_restore().transpose(..., "time", "c", "v")
if len(da.time) == 1: # remove "time dimension" for static case
return da.isel({"time": 0})
return da
def _interp_time_coordinates(self, time: Time) -> xr.DataArray:
"""Interpolate the coordinates in time."""
if isinstance(self.coordinates, TimeSeries):
time_interp = Time(time, self.reference_time)
coordinates = self._coords_from_discrete_time_series(
self.coordinates.interp_time(time_interp)
)
if self.has_reference_time:
coordinates.weldx.time_ref = self.reference_time
return coordinates
if "time" not in self.coordinates.dims: # don't interpolate static
return self.coordinates
if time.max() <= self.time.min(): # only use edge timestamp
return self.coordinates.isel(time=0).data
if time.min() >= self.time.max(): # only use edge timestamp
return self.coordinates.isel(time=-1).data
# full interpolation with overlapping times
return ut.xr_interp_coordinates_in_time(self.coordinates, time)