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from typing import Tuple
import numpy as np
import numpy.typing as npt
import xarray as xr
from sarsen import geocoding, orbit
def test_secant_method() -> None:
def ufunc(
t: npt.ArrayLike,
) -> Tuple[npt.NDArray[np.float64], npt.NDArray[np.float64]]:
ft: npt.NDArray[np.float64] = np.asarray(t).astype("float64")
retval = 1.0 + 0.015 * ft - 0.0001 * ft**2 + 0.00003 * ft**3
return retval, retval
t_start: npt.NDArray[np.timedelta64] = np.array([np.timedelta64(-100, "ns")])
# stop with df threshold
res, _, _, _ = geocoding.secant_method(ufunc, -t_start, t_start, diff_ufunc=0.1)
assert isinstance(res, np.ndarray)
assert res.size == 1
assert res[0] == np.timedelta64(-27, "ns")
# stop with dt threshold
res, _, _, _ = geocoding.secant_method(ufunc, -t_start, t_start, diff_ufunc=0.01)
assert res[0] == np.timedelta64(-27, "ns")
t_start = np.ones((2, 2), dtype="timedelta64[ns]") * 100 # type: ignore
res, _, _, _ = geocoding.secant_method(ufunc, -t_start, t_start, diff_ufunc=0.1)
assert res.shape == t_start.shape
assert np.all(res == np.timedelta64(-27, "ns"))
def test_zero_doppler_plane_distance(
dem_ecef: xr.DataArray, orbit_ds: xr.Dataset
) -> None:
orbit_interpolator = orbit.OrbitPolyfitIterpolator.from_position(orbit_ds.position)
res0, (res1, res2) = geocoding.zero_doppler_plane_distance(
dem_ecef,
orbit_interpolator.position(),
orbit_interpolator.velocity(),
orbit_ds.azimuth_time,
)
assert isinstance(res0, xr.DataArray)
assert isinstance(res1, xr.DataArray)
assert isinstance(res2, xr.DataArray)
def test_backward_geocode(dem_ecef: xr.DataArray, orbit_ds: xr.Dataset) -> None:
orbit_interpolator = orbit.OrbitPolyfitIterpolator.from_position(orbit_ds.position)
res = geocoding.backward_geocode(
dem_ecef,
orbit_interpolator.position(),
orbit_interpolator.velocity(),
)
assert isinstance(res, xr.Dataset)
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