Ruff-ALL streams.py

ioos_qc/axds.py

@@ -67,11 +67,7 @@ def valid_range_test(
     # This is required because we don't want to restrict a user from using a pd.Series
     # directly with this function. If the data was coming from a Store, it would
     # always be a numpy array.
-    elif (
-        dtype is None
-        and hasattr(inp, "values")
-        and hasattr(inp.values, "dtype")
-    ):
+    elif dtype is None and hasattr(inp, "values") and hasattr(inp.values, "dtype"):
         dtype = inp.values.dtype
 
     # Save original shape

ioos_qc/config.py

@@ -158,13 +158,9 @@ def run(self, **passedkwargs):
         # Get the arguments that the test functions support
         sig = signature(self.func)
         valid_keywords = [
-            p.name
-            for p in sig.parameters.values()
-            if p.kind == p.POSITIONAL_OR_KEYWORD
+            p.name for p in sig.parameters.values() if p.kind == p.POSITIONAL_OR_KEYWORD
         ]
-        testkwargs = {
-            k: v for k, v in testkwargs.items() if k in valid_keywords
-        }
+        testkwargs = {k: v for k, v in testkwargs.items() if k in valid_keywords}
         try:
             results.append(
                 CallResult(
@@ -320,11 +316,7 @@ def calls(self):
 
     @property
     def aggregate_calls(self):
-        return [
-            c
-            for c in self._calls
-            if hasattr(c.func, "aggregate") and c.func.aggregate is True
-        ]
+        return [c for c in self._calls if hasattr(c.func, "aggregate") and c.func.aggregate is True]
 
     def has(self, stream_id: str, method: Union[callable, str]):
         if isinstance(method, str):
@@ -422,10 +414,7 @@ def __init__(self, source: ConfigTypes) -> None:
             elif self.config["region"] and "features" in self.config["region"]:
                 # Feature based GeoJSON
                 self.region = GeometryCollection(
-                    [
-                        shape(feature["geometry"])
-                        for feature in self.config["region"]["features"]
-                    ],
+                    [shape(feature["geometry"]) for feature in self.config["region"]["features"]],
                 )
             elif self.config["region"] and "geometry" in self.config["region"]:
                 # Geometry based GeoJSON

ioos_qc/config_creator/config_creator.py

@@ -304,10 +304,7 @@ def create_config(self, variable_config):
     def _load_datasets(self):
         """Load datasets."""
         L.debug(f"Loading {len(self.config)} datasets...")
-        return {
-            name: xr.load_dataset(self.config[name]["file_path"])
-            for name in self.config
-        }
+        return {name: xr.load_dataset(self.config[name]["file_path"]) for name in self.config}
 
     def _determine_dataset_years(self):
         """Determine year used in datasets, return as dict {dataset_name, year}.

ioos_qc/config_creator/get_assets.py

@@ -102,9 +102,7 @@ def ocean_atlas_variable_enhance(output_dir, month) -> None:
 
 def ocean_atlas_merge_time(output_dir) -> None:
     variable_merged_files = output_dir.glob("ocean_atlas_??.nc")
-    variable_merged_files = [
-        str(merged_file) for merged_file in list(variable_merged_files)
-    ]
+    variable_merged_files = [str(merged_file) for merged_file in list(variable_merged_files)]
     variable_merged_files.sort()
     output_file = output_dir.parent / "ocean_atlas.nc"
 

ioos_qc/qartod.py

@@ -174,12 +174,9 @@ def location_test(
     # Ignore warnings when comparing NaN values even though they are masked
     # https://github.com/numpy/numpy/blob/master/doc/release/1.8.0-notes.rst#runtime-warnings-when-comparing-nan-numbers
     with np.errstate(invalid="ignore"):
-        flag_arr[
-            (lon < bbox.minx)
-            | (lat < bbox.miny)
-            | (lon > bbox.maxx)
-            | (lat > bbox.maxy)
-        ] = QartodFlags.FAIL
+        flag_arr[(lon < bbox.minx) | (lat < bbox.miny) | (lon > bbox.maxx) | (lat > bbox.maxy)] = (
+            QartodFlags.FAIL
+        )
 
     return flag_arr.reshape(original_shape)
 
@@ -238,9 +235,7 @@ def gross_range_test(
             raise ValueError(msg)
         # Flag suspect outside of user span
         with np.errstate(invalid="ignore"):
-            flag_arr[(inp < uspan.minv) | (inp > uspan.maxv)] = (
-                QartodFlags.SUSPECT
-            )
+            flag_arr[(inp < uspan.minv) | (inp > uspan.maxv)] = QartodFlags.SUSPECT
 
     # Flag suspect outside of sensor span
     with np.errstate(invalid="ignore"):
@@ -421,11 +416,7 @@ def check(self, tinp, inp, zinp):
                 # Only test non-masked values between the min and max.
                 # Ignore warnings about comparing masked values
                 with np.errstate(invalid="ignore"):
-                    z_idx = (
-                        (~zinp.mask)
-                        & (zinp >= m.zspan.minv)
-                        & (zinp <= m.zspan.maxv)
-                    )
+                    z_idx = (~zinp.mask) & (zinp >= m.zspan.minv) & (zinp <= m.zspan.maxv)
             else:
                 # If there is no z data in the config, don't try to filter by depth!
                 # Set z_idx to all True to prevent filtering
@@ -451,12 +442,8 @@ def check(self, tinp, inp, zinp):
 
             with np.errstate(invalid="ignore"):
                 flag_arr[(values_idx & fail_idx)] = QartodFlags.FAIL
-                flag_arr[(values_idx & ~fail_idx & suspect_idx)] = (
-                    QartodFlags.SUSPECT
-                )
-                flag_arr[(values_idx & ~fail_idx & ~suspect_idx)] = (
-                    QartodFlags.GOOD
-                )
+                flag_arr[(values_idx & ~fail_idx & suspect_idx)] = QartodFlags.SUSPECT
+                flag_arr[(values_idx & ~fail_idx & ~suspect_idx)] = QartodFlags.GOOD
 
         return flag_arr
 
@@ -752,9 +739,7 @@ def flat_line_test(
     tinp = mapdates(tinp).flatten()
 
     # The thresholds are in seconds so we round make sure the interval is also in seconds
-    time_interval = (
-        np.median(np.diff(tinp)).astype("timedelta64[s]").astype(float)
-    )
+    time_interval = np.median(np.diff(tinp)).astype("timedelta64[s]").astype(float)
 
     def rolling_window(a, window):
         """https://rigtorp.se/2011/01/01/rolling-statistics-numpy.html."""
@@ -880,9 +865,7 @@ def window_func(w):
         if min_obs is not None:
             min_periods = min_obs
         elif min_period is not None:
-            time_interval = (
-                np.median(np.diff(tinp)).astype("timedelta64[s]").astype(float)
-            )
+            time_interval = np.median(np.diff(tinp)).astype("timedelta64[s]").astype(float)
             min_periods = (min_period / time_interval).astype(int)
         else:
             min_periods = None

ioos_qc/results.py

@@ -50,7 +50,9 @@ class CollectedResult:
     lon: np.ndarray = None
 
     def __repr__(self) -> str:
-        return f"<CollectedResult stream_id={self.stream_id} package={self.package} test={self.test}>"
+        return (
+            f"<CollectedResult stream_id={self.stream_id} package={self.package} test={self.test}>"
+        )
 
     def function_name(self) -> str:
         return self.function.__name__
@@ -178,8 +180,6 @@ def collect_results_dict(results):
                 collected[r.stream_id][testpackage][testname] = np.copy(
                     flag_arr,
                 )
-            collected[r.stream_id][testpackage][testname][r.subset_indexes] = (
-                testresults
-            )
+            collected[r.stream_id][testpackage][testname][r.subset_indexes] = testresults
 
     return collected

ioos_qc/stores.py

@@ -132,9 +132,7 @@ def save(
 
             # Exclusion list, skip everything defined
             if exclude is not None and (
-                cr.function in exclude
-                or cr.stream_id in exclude
-                or cr.test in cr.test in include
+                cr.function in exclude or cr.stream_id in exclude or cr.test in cr.test in include
             ):
                 continue
 
@@ -223,9 +221,7 @@ def save(
 
             # Get flags from module attribute called FLAGS
             flags = inspect.getmodule(cr.function).FLAGS
-            varflagnames = [
-                d for d in flags.__dict__ if not d.startswith("__")
-            ]
+            varflagnames = [d for d in flags.__dict__ if not d.startswith("__")]
             varflagvalues = [getattr(flags, d) for d in varflagnames]
 
             # Set QC variable attributes
@@ -247,11 +243,7 @@ def save(
                 if len(config.contexts) == 1:
                     calls = config.calls_by_stream_id(cr.stream_id)
 
-                    calls = [
-                        c
-                        for c in calls
-                        if c.module == cr.package and c.method == cr.test
-                    ]
+                    calls = [c for c in calls if c.module == cr.package and c.method == cr.test]
                     if not calls:
                         # No stream_id found!
                         continue
@@ -372,12 +364,8 @@ def save(self, path_or_ncd, config, results):
 
                         # Get flags from module attribute called FLAGS
                         flags = testpackage.FLAGS
-                        varflagnames = [
-                            d for d in flags.__dict__ if not d.startswith("__")
-                        ]
-                        varflagvalues = [
-                            getattr(flags, d) for d in varflagnames
-                        ]
+                        varflagnames = [d for d in flags.__dict__ if not d.startswith("__")]
+                        varflagvalues = [getattr(flags, d) for d in varflagnames]
 
                         if qcvarname not in ncd.variables:
                             v = ncd.createVariable(
@@ -412,11 +400,7 @@ def save(self, path_or_ncd, config, results):
                         v.setncattr("ioos_qc_target", vname)
                         # If there is only one context we can write variable specific configs
                         if len(config.contexts) == 1:
-                            varconfig = (
-                                config.contexts[0]
-                                .streams[vname]
-                                .config[modu][testname]
-                            )
+                            varconfig = config.contexts[0].streams[vname].config[modu][testname]
                             varconfig = json.dumps(
                                 varconfig,
                                 cls=GeoNumpyDateEncoder,