orbitx.utils._orbit.interpolate_orbit.interpolate_orbit#
- orbitx.utils._orbit.interpolate_orbit.interpolate_orbit(start_date: datetime64, end_date: datetime64, sat_sec_since: ndarray[tuple[Any, ...], dtype[_ScalarT]], sat_lat_sim: ndarray[tuple[Any, ...], dtype[_ScalarT]], sat_lon_sim: ndarray[tuple[Any, ...], dtype[_ScalarT]], interpolation_sampling_interval: timedelta64, reference_date: datetime64 = np.datetime64('1970-01-01T00:00:00')) Tuple[ndarray[tuple[Any, ...], dtype[float64]], ndarray[tuple[Any, ...], dtype[datetime64]], ndarray[tuple[Any, ...], dtype[float64]], ndarray[tuple[Any, ...], dtype[float64]]][source]#
interpolate_orbit Interpolate the orbit at desired time resolution
Used to interpolate the physics-simulated orbits at a sufficiently high resolution
- Parameters:
start_date (np.datetime64)
end_date (np.datetime64)
sat_sec_since (npt.NDArray)
sat_lat_sim (npt.NDArray)
sat_lon_sim (npt.NDArray)
interpolation_sampling_interval (np.timedelta64)
reference_date (_type_, optional)
start_date – The date from which the orbit should be interpolated
end_date – The date until which the orbit should be simulated
sat_sec_since – The times at which the orbits were simulated with physics (in seconds since a reference date)
sat_lat_sim – The simulated latitudes of the satellites
sat_lon_sim – The simulated longitudes of the satellites
interpolation_sampling_interval – The time lapse between two successive interpolation times
reference_date – The time variables are given in seconds since a reference date. This input sets the reference date used. Defaults to np.datetime64(“1970-01-01T00:00:00”).
- Returns:
- Return type:
Tuple[npt.NDArray, npt.NDArray, npt.NDArray, npt.NDArray]
- Returns:
A tuple containing the times at which the interpolated values are obtained (in seconds since the reference date), and the times at which the interpolated values are obtained (in numpy datetime64 format), the interpolated latitude, the interpolated longitude
- Return type:
Tuple[ npt.NDArray[np.float64], npt.NDArray[np.datetime64], npt.NDArray[np.float64], npt.NDArray[np.float64], ]