Temporal res

c3s_eqc_data_checker/check.py

@@ -296,23 +296,26 @@ def check_temporal_resolution(
         self,
         min: datetime.date | datetime.datetime | str | None,
         max: datetime.date | datetime.datetime | str | None,
-        resolution: str | None,
+        frequency: str | None,
         name: str | None,
     ) -> dict[str, Any]:  # noqa: D205, D400
         """
         [temporal_resolution]
         # Check temporal resolution.
         #
+        # See pandas frequency aliases:
+        # https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#timeseries-offset-aliases
+        #
         # Arguments:
         #   * min: first time (optional)
         #   * max: last time (optional)
-        #   * resolution: time resolution (optional)
+        #   * frequency: time frequency (optional).
         #   * name: name of time dimension (optional, default: "time")
         #
         # Example:
         min = 1900-01-01
         max = 1900-01-02
-        resolution = "1 days"
+        frequency = "1D"
         name = "time"
         """
         if name is None:
@@ -334,12 +337,12 @@ def check_temporal_resolution(
             if (actual_max := time.max()) != pd.to_datetime(max):
                 errors["max"] = str(actual_max.values)
 
-        if resolution is not None:
-            res_td = pd.to_timedelta(resolution)
-            if time.size <= 1 and res_td != pd.to_timedelta(0):
-                errors["resolution"] = "0"
-            elif ((actual_res := time.diff(name)) != res_td).any():
-                errors["resolution"] = {str(value) for value in actual_res.values}
+        if frequency is not None:
+            expected_time = pd.date_range(
+                time.min().values, time.max().values, freq=frequency
+            )
+            if time.size != expected_time.size or not (time == expected_time).all():
+                errors["frequency"] = {str(value) for value in time.diff(name).values}
 
         return errors
 

tests/test_10_netcdf.py

@@ -73,19 +73,21 @@ def test_cf_compliance(tmp_path: pathlib.Path) -> None:
 
 
 def test_temporal_resolution(tmp_path: pathlib.Path) -> None:
-    for date in pd.date_range("1900-01-01", "1900-01-02", freq="1D"):
+    for date in pd.date_range("1900-01-01", "1900-02-01", freq="1MS"):
         da = xr.DataArray(date, name="time")
         da.to_netcdf(tmp_path / f"{date}.nc")
 
     checker = Checker(str(tmp_path / "*.nc"), files_format="NETCDF")
-    actual = checker.check_temporal_resolution("1900-01-01", "1900-01-02", "1D", "time")
+    actual = checker.check_temporal_resolution(
+        "1900-01-01", "1900-02-01", "1MS", "time"
+    )
     assert actual == {}
 
-    actual = checker.check_temporal_resolution("2000-01-01", "2000-01-02", "2D", "time")
+    actual = checker.check_temporal_resolution("2000-01-01", "2000-02-01", "1D", "time")
     expected = {
         "min": "1900-01-01T00:00:00.000000000",
-        "max": "1900-01-02T00:00:00.000000000",
-        "resolution": {"86400000000000 nanoseconds"},
+        "max": "1900-02-01T00:00:00.000000000",
+        "frequency": {"2678400000000000 nanoseconds"},
     }
     assert actual == expected
 

tests/test_20_grib.py

@@ -71,7 +71,7 @@ def test_cf_compliance(tmp_path: pathlib.Path, grib_path: pathlib.Path) -> None:
 def test_temporal_resolution(grib_path: pathlib.Path) -> None:
     checker = Checker(str(grib_path / "GRIB2.tmpl"), files_format="GRIB")
     actual = checker.check_temporal_resolution(
-        "2007-03-23T12", "2007-03-23T12", "0", None
+        "2007-03-23T12", "2007-03-23T12", None, None
     )
     assert actual == {}
 
@@ -81,7 +81,6 @@ def test_temporal_resolution(grib_path: pathlib.Path) -> None:
     expected = {
         "max": "2007-03-23T12:00:00.000000000",
         "min": "2007-03-23T12:00:00.000000000",
-        "resolution": "0",
     }
     assert actual == expected