From 9653a012a49ce54e9e1ef25b815ecfad8b960b72 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Kai=20M=C3=BChlbauer?= <kai.muehlbauer@uni-bonn.de>
Date: Tue, 10 Dec 2024 13:57:33 +0100
Subject: [PATCH] fix tests after merge

---
 xarray/tests/test_variable.py | 58 ++++++++++++++++++++---------------
 1 file changed, 34 insertions(+), 24 deletions(-)

diff --git a/xarray/tests/test_variable.py b/xarray/tests/test_variable.py
index 6c5fc3ac9e1..32c4f8130d6 100644
--- a/xarray/tests/test_variable.py
+++ b/xarray/tests/test_variable.py
@@ -275,33 +275,43 @@ def test_0d_time_data(self):
         expected = np.datetime64("2000-01-01", "ns")
         assert x[0].values == expected
 
+    dt64_data = pd.date_range("2000-01-01", periods=3)
+
     @pytest.mark.filterwarnings("ignore:Converting non-default")
-    def test_datetime64_conversion(self):
-        times = pd.date_range("2000-01-01", periods=3)
-        for values in [
-            times,
-            times.values,
-            times.values.astype("datetime64[s]"),
-            times.to_pydatetime(),
-        ]:
-            v = self.cls(["t"], values)
-            assert v.dtype == np.dtype("datetime64[ns]")
-            assert_array_equal(v.values, times.values)
-            assert v.values.dtype == np.dtype("datetime64[ns]")
+    @pytest.mark.parametrize(
+        "values, unit",
+        [
+            (dt64_data, "ns"),
+            (dt64_data.values, "ns"),
+            (dt64_data.values.astype("datetime64[s]"), "s"),
+            (dt64_data.to_pydatetime(), "ns"),
+        ],
+    )
+    def test_datetime64_conversion(self, values, unit):
+        # todo: check, if this test is OK
+        v = self.cls(["t"], values)
+        assert v.dtype == np.dtype(f"datetime64[{unit}]")
+        assert_array_equal(v.values, self.dt64_data.values)
+        assert v.values.dtype == np.dtype(f"datetime64[{unit}]")
+
+    td64_data = pd.timedelta_range(start=0, periods=3)
 
     @pytest.mark.filterwarnings("ignore:Converting non-default")
-    def test_timedelta64_conversion(self):
-        times = pd.timedelta_range(start=0, periods=3)
-        for values in [
-            times,
-            times.values,
-            times.values.astype("timedelta64[s]"),
-            times.to_pytimedelta(),
-        ]:
-            v = self.cls(["t"], values)
-            assert v.dtype == np.dtype("timedelta64[ns]")
-            assert_array_equal(v.values, times.values)
-            assert v.values.dtype == np.dtype("timedelta64[ns]")
+    @pytest.mark.parametrize(
+        "values, unit",
+        [
+            (td64_data, "ns"),
+            (td64_data.values, "ns"),
+            (td64_data.values.astype("timedelta64[s]"), "s"),
+            (td64_data.to_pytimedelta(), "ns"),
+        ],
+    )
+    def test_timedelta64_conversion(self, values, unit):
+        # todo: check, if this test is OK
+        v = self.cls(["t"], values)
+        assert v.dtype == np.dtype(f"timedelta64[{unit}]")
+        assert_array_equal(v.values, self.td64_data.values)
+        assert v.values.dtype == np.dtype(f"timedelta64[{unit}]")
 
     def test_object_conversion(self):
         data = np.arange(5).astype(str).astype(object)