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Merged
merged 4 commits into from
Oct 31, 2025
Merged

Adding invdistland interpolator #2350

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d1ee511
Reshaping return array of _get_corner_data_Agrid to (ti, zi, yi, xi, …
erikvansebille Oct 29, 2025
6392d0e
Adding XLinearInvdistLandTracer interpolator
erikvansebille Oct 29, 2025
5dc1c55
Vectorized version of XLinearInvdistLandTracer interpolator
erikvansebille Oct 30, 2025
60dd863
Merge branch 'v4-dev' into interpolator_invdistland
erikvansebille Oct 31, 2025
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77 changes: 62 additions & 15 deletions src/parcels/interpolators.py
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Original file line number Diff line number Diff line change
Expand Up @@ -22,6 +22,7 @@
"UXPiecewiseLinearNode",
"XFreeslip",
"XLinear",
"XLinearInvdistLandTracer",
"XNearest",
"XPartialslip",
"ZeroInterpolator",
Expand Down Expand Up @@ -75,11 +76,11 @@ def _get_corner_data_Agrid(

# Y coordinates: [yi, yi, yi+1, yi+1] for each spatial point, repeated for time/z
yi_1 = np.clip(yi + 1, 0, data.shape[2] - 1)
yi = np.tile(np.repeat(np.column_stack([yi, yi_1]), 2), (lenT) * (lenZ))
yi = np.tile(np.array([yi, yi, yi_1, yi_1]).flatten(), lenT * lenZ)

# X coordinates: [xi, xi+1, xi, xi+1] for each spatial point, repeated for time/z
xi_1 = np.clip(xi + 1, 0, data.shape[3] - 1)
xi = np.tile(np.column_stack([xi, xi_1, xi, xi_1]).flatten(), (lenT) * (lenZ))
xi = np.tile(np.array([xi, xi_1]).flatten(), lenT * lenZ * 2)

# Create DataArrays for indexing
selection_dict = {
Expand All @@ -91,7 +92,7 @@ def _get_corner_data_Agrid(
if "time" in data.dims:
selection_dict["time"] = xr.DataArray(ti, dims=("points"))

return data.isel(selection_dict).data.reshape(lenT, lenZ, npart, 4)
return data.isel(selection_dict).data.reshape(lenT, lenZ, 2, 2, npart)


def XLinear(
Expand All @@ -114,22 +115,22 @@ def XLinear(
corner_data = _get_corner_data_Agrid(data, ti, zi, yi, xi, lenT, lenZ, len(xsi), axis_dim)

if lenT == 2:
tau = tau[np.newaxis, :, np.newaxis]
corner_data = corner_data[0, :, :, :] * (1 - tau) + corner_data[1, :, :, :] * tau
tau = tau[np.newaxis, :]
corner_data = corner_data[0, :] * (1 - tau) + corner_data[1, :] * tau
else:
corner_data = corner_data[0, :, :, :]
corner_data = corner_data[0, :]

if lenZ == 2:
zeta = zeta[:, np.newaxis]
corner_data = corner_data[0, :, :] * (1 - zeta) + corner_data[1, :, :] * zeta
zeta = zeta[np.newaxis, :]
corner_data = corner_data[0, :] * (1 - zeta) + corner_data[1, :] * zeta
else:
corner_data = corner_data[0, :, :]
corner_data = corner_data[0, :]

value = (
(1 - xsi) * (1 - eta) * corner_data[:, 0]
+ xsi * (1 - eta) * corner_data[:, 1]
+ (1 - xsi) * eta * corner_data[:, 2]
+ xsi * eta * corner_data[:, 3]
(1 - xsi) * (1 - eta) * corner_data[0, 0, :]
+ xsi * (1 - eta) * corner_data[0, 1, :]
+ (1 - xsi) * eta * corner_data[1, 0, :]
+ xsi * eta * corner_data[1, 1, :]
)
return value.compute() if is_dask_collection(value) else value

Expand Down Expand Up @@ -409,8 +410,8 @@ def _Spatialslip(
corner_dataV = _get_corner_data_Agrid(vectorfield.V.data, ti, zi, yi, xi, lenT, lenZ, npart, axis_dim)

def is_land(ti: int, zi: int, yi: int, xi: int):
uval = corner_dataU[ti, zi, :, xi + 2 * yi]
vval = corner_dataV[ti, zi, :, xi + 2 * yi]
uval = corner_dataU[ti, zi, yi, xi, :]
vval = corner_dataV[ti, zi, yi, xi, :]
return np.where(np.isclose(uval, 0.0) & np.isclose(vval, 0.0), True, False)

f_u = np.ones_like(xsi)
Expand Down Expand Up @@ -571,6 +572,52 @@ def XNearest(
return value.compute() if is_dask_collection(value) else value


def XLinearInvdistLandTracer(
particle_positions: dict[str, float | np.ndarray],
grid_positions: dict[_XGRID_AXES, dict[str, int | float | np.ndarray]],
field: Field,
):
"""Linear spatial interpolation on a regular grid, where points on land are not used."""
values = XLinear(particle_positions, grid_positions, field)

xi, xsi = grid_positions["X"]["index"], grid_positions["X"]["bcoord"]
yi, eta = grid_positions["Y"]["index"], grid_positions["Y"]["bcoord"]
zi, zeta = grid_positions["Z"]["index"], grid_positions["Z"]["bcoord"]
ti, tau = grid_positions["T"]["index"], grid_positions["T"]["bcoord"]

axis_dim = field.grid.get_axis_dim_mapping(field.data.dims)
lenT = 2 if np.any(tau > 0) else 1
lenZ = 2 if np.any(zeta > 0) else 1

corner_data = _get_corner_data_Agrid(field.data, ti, zi, yi, xi, lenT, lenZ, len(xsi), axis_dim)

land_mask = np.isnan(corner_data)
nb_land = np.sum(land_mask, axis=(0, 1, 2, 3))

if np.any(nb_land):
all_land_mask = nb_land == 4 * lenZ * lenT
values[all_land_mask] = 0.0

not_all_land = ~all_land_mask
if np.any(not_all_land):
i_grid = np.arange(2)[None, None, None, :, None]
j_grid = np.arange(2)[None, None, :, None, None]
eta_b = eta[None, None, None, None, :]
xsi_b = xsi[None, None, None, None, :]

inv_dist = 1.0 / ((eta_b - j_grid) ** 2 + (xsi_b - i_grid) ** 2)

valid_mask = ~land_mask
weighted = np.where(valid_mask, corner_data * inv_dist, 0.0)

val = np.sum(weighted, axis=(0, 1, 2, 3))
w_sum = np.sum(np.where(valid_mask, inv_dist, 0.0), axis=(0, 1, 2, 3))

values[not_all_land] = val[not_all_land] / w_sum[not_all_land]

return values.compute() if is_dask_collection(values) else values


def UXPiecewiseConstantFace(
particle_positions: dict[str, float | np.ndarray],
grid_positions: dict[_UXGRID_AXES, dict[str, int | float | np.ndarray]],
Expand Down
45 changes: 44 additions & 1 deletion tests/test_interpolation.py
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Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -21,6 +21,7 @@
UXPiecewiseLinearNode,
XFreeslip,
XLinear,
XLinearInvdistLandTracer,
XNearest,
XPartialslip,
ZeroInterpolator,
Expand Down Expand Up @@ -68,9 +69,19 @@ def field():
[0.49, 0.49],
[0.51, 0.51],
[1.49, 6.49],
id="Linear",
id="Linear-1",
),
pytest.param(XLinear, np.timedelta64(1, "s"), 2.5, 0.49, 0.51, 13.99, id="Linear-2"),
pytest.param(
XLinear,
[np.timedelta64(0, "s"), np.timedelta64(1, "s"), np.timedelta64(1, "s")],
[0, 0, 2.5],
[0.49, 0.49, 0.49],
[0.51, 0.51, 0.51],
[1.49, 6.49, 13.99],
id="Linear-3",
),
pytest.param(XLinearInvdistLandTracer, np.timedelta64(1, "s"), 2.5, 0.49, 0.51, 13.99, id="LinearInvDistLand"),
pytest.param(
XNearest,
[np.timedelta64(0, "s"), np.timedelta64(3, "s")],
Expand Down Expand Up @@ -122,6 +133,38 @@ def test_spatial_slip_interpolation(field, func, t, z, y, x, expected):
np.testing.assert_array_almost_equal(velocities, expected)


@pytest.mark.parametrize(
"func, t, z, y, x, expected",
[
(XLinearInvdistLandTracer, np.timedelta64(1, "s"), 0, 0.5, 0.5, 1.0),
(XLinearInvdistLandTracer, np.timedelta64(1, "s"), 0, 1.5, 1.5, 0.0),
(
XLinearInvdistLandTracer,
[np.timedelta64(0, "s"), np.timedelta64(1, "s")],
[0, 2],
[0.5, 0.5],
[0.5, 0.5],
1.0,
),
(
XLinearInvdistLandTracer,
[np.timedelta64(0, "s"), np.timedelta64(1, "s")],
[0, 2],
[0.5, 1.5],
[0.5, 1.5],
[1.0, 0.0],
),
],
)
def test_invdistland_interpolation(field, func, t, z, y, x, expected):
field.data[:] = 1.0
field.data[:, :, 1:3, 1:3] = np.nan # Set NaN land value to test inv_dist
field.interp_method = func

value = field[t, z, y, x]
np.testing.assert_array_almost_equal(value, expected)


@pytest.mark.parametrize("mesh", ["spherical", "flat"])
def test_interpolation_mesh_type(mesh, npart=10):
ds = simple_UV_dataset(mesh=mesh)
Expand Down