Making _search_time_index return a dictionary like grid.search

Author: erikvansebille

src/parcels/_core/field.py

@@ -217,7 +217,7 @@ def eval(self, time: datetime, z, y, x, particles=None, applyConversion=True):
             _ei = particles.ei[:, self.igrid]
 
         position = {"time": time, "z": z, "lat": y, "lon": x}
-        (position["ti"], position["tau"]) = _search_time_index(self, time)
+        position.update(_search_time_index(self, time))
         position.update(self.grid.search(z, y, x, ei=_ei))
         _update_particles_ei(particles, position, self)
         _update_particle_states_position(particles, position)
@@ -302,7 +302,7 @@ def eval(self, time: datetime, z, y, x, particles=None, applyConversion=True):
             _ei = particles.ei[:, self.igrid]
 
         position = {"time": time, "z": z, "lat": y, "lon": x}
-        (position["ti"], position["tau"]) = _search_time_index(self.U, time)
+        position.update(_search_time_index(self.U, time))
         position.update(self.grid.search(z, y, x, ei=_ei))
         _update_particles_ei(particles, position, self)
         _update_particle_states_position(particles, position)

src/parcels/_core/index_search.py

@@ -75,14 +75,14 @@ def _search_time_index(field: Field, time: datetime):
     if the sampled value is outside the time value range.
     """
     if field.time_interval is None:
-        return np.zeros(shape=time.shape, dtype=np.int32), np.zeros(shape=time.shape, dtype=np.float32)
+        return {"ti": np.zeros(shape=time.shape, dtype=np.int32), "tau": np.zeros(shape=time.shape, dtype=np.float32)}
 
     if not field.time_interval.is_all_time_in_interval(time):
         _raise_time_extrapolation_error(time, field=None)
 
     ti = np.searchsorted(field.data.time.data, time, side="right") - 1
     tau = (time - field.data.time.data[ti]) / (field.data.time.data[ti + 1] - field.data.time.data[ti])
-    return np.atleast_1d(ti), np.atleast_1d(tau)
+    return {"ti": np.atleast_1d(ti), "tau": np.atleast_1d(tau)}
 
 
 def curvilinear_point_in_cell(grid, y: np.ndarray, x: np.ndarray, yi: np.ndarray, xi: np.ndarray):

tests/test_interpolation.py

@@ -85,7 +85,7 @@ def field():
 def test_raw_2d_interpolation(field, func, t, z, y, x, expected):
     """Test the interpolation functions on the Field."""
     position = field.grid.search(z, y, x)
-    (position["ti"], position["tau"]) = _search_time_index(field, t)
+    position.update(_search_time_index(field, t))
 
     value = func(position, field)
     np.testing.assert_equal(value, expected)