Minor test cleanup (#45)

Author: dcherian

cf_xarray/tests/datasets.py

@@ -70,3 +70,12 @@
     1e-3, attrs=dict(standard_name="specific_humidity detection_minimum", units="g/g"),
 )
 anc
+
+multiple = xr.Dataset()
+multiple.coords["x1"] = ("x1", range(30), {"axis": "X"})
+multiple.coords["y1"] = ("y1", range(20), {"axis": "Y"})
+multiple.coords["x2"] = ("x2", range(10), {"axis": "X"})
+multiple.coords["y2"] = ("y2", range(5), {"axis": "Y"})
+
+multiple["v1"] = (("x1", "y1"), np.ones((30, 20)) * 15)
+multiple["v2"] = (("x2", "y2"), np.ones((10, 5)) * 15)

cf_xarray/tests/test_accessor.py

@@ -1,14 +1,13 @@
 import matplotlib as mpl
 import matplotlib.pyplot as plt
-import numpy as np
 import pytest
 import xarray as xr
 from xarray.testing import assert_identical
 
 import cf_xarray  # noqa
 
 from . import raise_if_dask_computes
-from .datasets import airds, anc, ds_no_attrs, popds
+from .datasets import airds, anc, ds_no_attrs, multiple, popds
 
 mpl.use("Agg")
 
@@ -119,25 +118,16 @@ def test_kwargs_methods(obj):
 
 def test_kwargs_expand_key_to_multiple_keys():
 
-    ds = xr.Dataset()
-    ds.coords["x1"] = ("x1", range(30), {"axis": "X"})
-    ds.coords["y1"] = ("y1", range(20), {"axis": "Y"})
-    ds.coords["x2"] = ("x2", range(10), {"axis": "X"})
-    ds.coords["y2"] = ("y2", range(5), {"axis": "Y"})
-
-    ds["v1"] = (("x1", "y1"), np.ones((30, 20)) * 15)
-    ds["v2"] = (("x2", "y2"), np.ones((10, 5)) * 15)
-
-    actual = ds.cf.isel(X=5, Y=3)
-    expected = ds.isel(x1=5, y1=3, x2=5, y2=3)
+    actual = multiple.cf.isel(X=5, Y=3)
+    expected = multiple.isel(x1=5, y1=3, x2=5, y2=3)
     assert_identical(actual, expected)
 
-    actual = ds.cf.mean("X")
-    expected = ds.mean(["x1", "x2"])
+    actual = multiple.cf.mean("X")
+    expected = multiple.mean(["x1", "x2"])
     assert_identical(actual, expected)
 
-    actual = ds.cf.coarsen(X=10, Y=5)
-    expected = ds.coarsen(x1=10, y1=5, x2=10, y2=5)
+    actual = multiple.cf.coarsen(X=10, Y=5)
+    expected = multiple.coarsen(x1=10, y1=5, x2=10, y2=5)
     assert_identical(actual.mean(), expected.mean())