Fix time encoding regression

Author: spencerkclark

doc/whats-new.rst

@@ -38,6 +38,11 @@ Deprecations
 Bug fixes
 ~~~~~~~~~
 
+- Fix datetime encoding precision loss regression introduced in previous
+  release for datetimes encoded with units requiring floating point values, and
+  a reference date not equal to the minimum of the datetime array
+  (:issue:`8271`). By `Spencer Clark <https://github.com/spencerkclark>`_.
+
 
 Documentation
 ~~~~~~~~~~~~~

xarray/coding/times.py

@@ -714,7 +714,8 @@ def encode_cf_datetime(
         if data_units != units:
             # this accounts for differences in the reference times
             ref_delta = abs(data_ref_date - ref_date).to_timedelta64()
-            if ref_delta > np.timedelta64(0, "ns"):
+            data_delta = _time_units_to_timedelta64(needed_units)
+            if (ref_delta % data_delta) > np.timedelta64(0, "ns"):
                 needed_units = _infer_time_units_from_diff(ref_delta)
 
         # needed time delta to encode faithfully to int64

xarray/tests/test_coding_times.py

@@ -1363,18 +1363,23 @@ def test_roundtrip_timedelta64_nanosecond_precision_warning() -> None:
 
 
 def test_roundtrip_float_times() -> None:
+    # Regression test for GitHub issue #8271
     fill_value = 20.0
-    times = [np.datetime64("2000-01-01 12:00:00", "ns"), np.datetime64("NaT", "ns")]
+    times = [
+        np.datetime64("1970-01-01 00:00:00", "ns"),
+        np.datetime64("1970-01-01 06:00:00", "ns"),
+        np.datetime64("NaT", "ns"),
+    ]
 
-    units = "days since 2000-01-01"
+    units = "days since 1960-01-01"
     var = Variable(
         ["time"],
         times,
         encoding=dict(dtype=np.float64, _FillValue=fill_value, units=units),
     )
 
     encoded_var = conventions.encode_cf_variable(var)
-    np.testing.assert_array_equal(encoded_var, np.array([0.5, 20.0]))
+    np.testing.assert_array_equal(encoded_var, np.array([3653, 3653.25, 20.0]))
     assert encoded_var.attrs["units"] == units
     assert encoded_var.attrs["_FillValue"] == fill_value