Move Field tests to separate file

parcels/_typing.py

@@ -26,7 +26,6 @@ class ParcelsAST(ast.AST):
     "bgrid_w_velocity",
     "cgrid_velocity",
     "linear_invdist_land_tracer",
-    "nearest",
     "bgrid_tracer",
     "cgrid_tracer",
 ]  # corresponds with `tracer_interp_method`

tests/test_advection.py

@@ -73,7 +73,6 @@ def test_advection_zonal(lon, lat, depth, mode):
     }
     dimensions = {"lon": lon, "lat": lat}
     fieldset2D = FieldSet.from_data(data2D, dimensions, mesh="spherical", transpose=True)
-    assert fieldset2D.U._creation_log == "from_data"
 
     pset2D = ParticleSet(fieldset2D, pclass=ptype[mode], lon=np.zeros(npart) + 20.0, lat=np.linspace(0, 80, npart))
     pset2D.execute(AdvectionRK4, runtime=timedelta(hours=2), dt=timedelta(seconds=30))

tests/test_field.py

@@ -0,0 +1,70 @@
+import cftime
+import numpy as np
+import pytest
+import xarray as xr
+
+from parcels import Field
+from parcels.tools.converters import (
+    _get_cftime_calendars,
+    _get_cftime_datetimes,
+)
+from tests.utils import TEST_DATA
+
+
+def test_field_from_netcdf_variables():
+    filename = str(TEST_DATA / "perlinfieldsU.nc")
+    dims = {"lon": "x", "lat": "y"}
+
+    variable = "vozocrtx"
+    f1 = Field.from_netcdf(filename, variable, dims)
+    variable = ("U", "vozocrtx")
+    f2 = Field.from_netcdf(filename, variable, dims)
+    variable = {"U": "vozocrtx"}
+    f3 = Field.from_netcdf(filename, variable, dims)
+
+    assert np.allclose(f1.data, f2.data, atol=1e-12)
+    assert np.allclose(f1.data, f3.data, atol=1e-12)
+
+    with pytest.raises(AssertionError):
+        variable = {"U": "vozocrtx", "nav_lat": "nav_lat"}  # multiple variables will fail
+        f3 = Field.from_netcdf(filename, variable, dims)
+
+
+@pytest.mark.parametrize("with_timestamps", [True, False])
+def test_field_from_netcdf(with_timestamps):
+    filenames = {
+        "lon": str(TEST_DATA / "mask_nemo_cross_180lon.nc"),
+        "lat": str(TEST_DATA / "mask_nemo_cross_180lon.nc"),
+        "data": str(TEST_DATA / "Uu_eastward_nemo_cross_180lon.nc"),
+    }
+    variable = "U"
+    dimensions = {"lon": "glamf", "lat": "gphif"}
+    if with_timestamps:
+        timestamp_types = [[[2]], [[np.datetime64("2000-01-01")]]]
+        for timestamps in timestamp_types:
+            Field.from_netcdf(filenames, variable, dimensions, interp_method="cgrid_velocity", timestamps=timestamps)
+    else:
+        Field.from_netcdf(filenames, variable, dimensions, interp_method="cgrid_velocity")
+
+
+@pytest.mark.parametrize(
+    "calendar, cftime_datetime", zip(_get_cftime_calendars(), _get_cftime_datetimes(), strict=True)
+)
+def test_field_nonstandardtime(calendar, cftime_datetime, tmpdir):
+    xdim = 4
+    ydim = 6
+    filepath = tmpdir.join("test_nonstandardtime.nc")
+    dates = [getattr(cftime, cftime_datetime)(1, m, 1) for m in range(1, 13)]
+    da = xr.DataArray(
+        np.random.rand(12, xdim, ydim), coords=[dates, range(xdim), range(ydim)], dims=["time", "lon", "lat"], name="U"
+    )
+    da.to_netcdf(str(filepath))
+
+    dims = {"lon": "lon", "lat": "lat", "time": "time"}
+    try:
+        field = Field.from_netcdf(filepath, "U", dims)
+    except NotImplementedError:
+        field = None
+
+    if field is not None:
+        assert field.grid.time_origin.calendar == calendar

tests/test_fieldset.py

@@ -4,7 +4,6 @@
 import sys
 from datetime import timedelta
 
-import cftime
 import dask
 import dask.array as da
 import numpy as np
@@ -29,8 +28,6 @@
     GeographicPolar,
     TimeConverter,
     UnitConverter,
-    _get_cftime_calendars,
-    _get_cftime_datetimes,
 )
 from tests.common_kernels import DoNothing
 from tests.utils import TEST_DATA
@@ -61,6 +58,7 @@ def test_fieldset_from_data(xdim, ydim):
     """Simple test for fieldset initialisation from data."""
     data, dimensions = generate_fieldset_data(xdim, ydim)
     fieldset = FieldSet.from_data(data, dimensions)
+    assert fieldset.U._creation_log == "from_data"
     assert len(fieldset.U.data.shape) == 3
     assert len(fieldset.V.data.shape) == 3
     assert np.allclose(fieldset.U.data[0, :], data["U"], rtol=1e-12)
@@ -139,65 +137,6 @@ def test_fieldset_from_parcels(xdim, ydim, tmpdir):
     assert np.allclose(fieldset.V.data[0, :], data["V"], rtol=1e-12)
 
 
-def test_field_from_netcdf_variables():
-    filename = str(TEST_DATA / "perlinfieldsU.nc")
-    dims = {"lon": "x", "lat": "y"}
-
-    variable = "vozocrtx"
-    f1 = Field.from_netcdf(filename, variable, dims)
-    variable = ("U", "vozocrtx")
-    f2 = Field.from_netcdf(filename, variable, dims)
-    variable = {"U": "vozocrtx"}
-    f3 = Field.from_netcdf(filename, variable, dims)
-
-    assert np.allclose(f1.data, f2.data, atol=1e-12)
-    assert np.allclose(f1.data, f3.data, atol=1e-12)
-
-    with pytest.raises(AssertionError):
-        variable = {"U": "vozocrtx", "nav_lat": "nav_lat"}  # multiple variables will fail
-        f3 = Field.from_netcdf(filename, variable, dims)
-
-
-@pytest.mark.parametrize(
-    "calendar, cftime_datetime", zip(_get_cftime_calendars(), _get_cftime_datetimes(), strict=True)
-)
-def test_fieldset_nonstandardtime(
-    calendar, cftime_datetime, tmpdir, filename="test_nonstandardtime.nc", xdim=4, ydim=6
-):
-    filepath = tmpdir.join(filename)
-    dates = [getattr(cftime, cftime_datetime)(1, m, 1) for m in range(1, 13)]
-    da = xr.DataArray(
-        np.random.rand(12, xdim, ydim), coords=[dates, range(xdim), range(ydim)], dims=["time", "lon", "lat"], name="U"
-    )
-    da.to_netcdf(str(filepath))
-
-    dims = {"lon": "lon", "lat": "lat", "time": "time"}
-    try:
-        field = Field.from_netcdf(filepath, "U", dims)
-    except NotImplementedError:
-        field = None
-
-    if field is not None:
-        assert field.grid.time_origin.calendar == calendar
-
-
-@pytest.mark.parametrize("with_timestamps", [True, False])
-def test_field_from_netcdf(with_timestamps):
-    filenames = {
-        "lon": str(TEST_DATA / "mask_nemo_cross_180lon.nc"),
-        "lat": str(TEST_DATA / "mask_nemo_cross_180lon.nc"),
-        "data": str(TEST_DATA / "Uu_eastward_nemo_cross_180lon.nc"),
-    }
-    variable = "U"
-    dimensions = {"lon": "glamf", "lat": "gphif"}
-    if with_timestamps:
-        timestamp_types = [[[2]], [[np.datetime64("2000-01-01")]]]
-        for timestamps in timestamp_types:
-            Field.from_netcdf(filenames, variable, dimensions, interp_method="cgrid_velocity", timestamps=timestamps)
-    else:
-        Field.from_netcdf(filenames, variable, dimensions, interp_method="cgrid_velocity")
-
-
 def test_fieldset_from_modulefile():
     nemo_fname = str(TEST_DATA / "fieldset_nemo.py")
     nemo_error_fname = str(TEST_DATA / "fieldset_nemo_error.py")