lint

CONTRIBUTING.md

@@ -245,5 +245,3 @@ importance of writing tested and maintainable software.
 
 * [How to Contribute to Open Source Guide](https://opensource.guide/how-to-contribute/)
 * [Zen of Scientific Software Maintenance](https://jrleeman.github.io/ScientificSoftwareMaintenance/)
-
-

LICENSE.txt

@@ -199,4 +199,3 @@ Apache License
    WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
    See the License for the specific language governing permissions and
    limitations under the License.
-

docs/source/conf.py

@@ -272,15 +272,12 @@
     # The paper size ('letterpaper' or 'a4paper').
     #
     # 'papersize': 'letterpaper',
-
     # The font size ('10pt', '11pt' or '12pt').
     #
     # 'pointsize': '10pt',
-
     # Additional stuff for the LaTeX preamble.
     #
     # 'preamble': '',
-
     # Latex figure (float) alignment
     #
     # 'figure_align': 'htbp',
@@ -290,8 +287,13 @@
 # (source start file, target name, title,
 #  author, documentclass [howto, manual, or own class]).
 latex_documents = [
-    (master_doc, "ioos_qc.tex", "ioos_qc Documentation",
-     "IOOS", "manual"),
+    (
+        master_doc,
+        "ioos_qc.tex",
+        "ioos_qc Documentation",
+        "IOOS",
+        "manual",
+    ),
 ]
 
 # The name of an image file (relative to this directory) to place at the top of

docs/source/examples/usage/Config.ipynb

@@ -111,4 +111,4 @@
    ]
   }
  ]
-}
+}

docs/source/examples/usage/ContextConfig.ipynb

@@ -97,4 +97,4 @@
    ]
   }
  ]
-}
+}

docs/source/examples/usage/NetcdfStream.ipynb

@@ -171,4 +171,4 @@
    ]
   }
  ]
-}
+}

docs/source/examples/usage/NumpyStream.ipynb

@@ -163,4 +163,4 @@
    ]
   }
  ]
-}
+}

docs/source/examples/usage/PandasStream.ipynb

@@ -207,4 +207,4 @@
    ]
   }
  ]
-}
+}

docs/source/examples/usage/XarrayStream.ipynb

@@ -177,4 +177,4 @@
    ]
   }
  ]
-}
+}

docs/source/installation.rst

@@ -4,4 +4,3 @@ Installation
 Install with `conda <https://docs.conda.io/en/latest/>`_::
 
     $ conda install -c conda-forge ioos_qc
-

docs/source/releases.rst

@@ -139,4 +139,3 @@ Specific changes to be aware of include:
 ####################
 
 See https://github.com/ioos/qartod and https://ioos.github.io/qartod/
-

ioos_qc/argo.py

@@ -1,5 +1,6 @@
 #!/usr/bin/env python
 """Tests based on the ARGO QC manual."""
+
 import logging
 import warnings
 from numbers import Real as N
@@ -13,8 +14,10 @@
 L = logging.getLogger(__name__)
 
 
-@add_flag_metadata(stanard_name="pressure_increasing_test_quality_flag",
-                   long_name="Pressure Increasing Test Quality Flag")
+@add_flag_metadata(
+    stanard_name="pressure_increasing_test_quality_flag",
+    long_name="Pressure Increasing Test Quality Flag",
+)
 def pressure_increasing_test(inp):
     """Returns an array of flag values where each input is flagged with SUSPECT if
     it does not monotonically increase.
@@ -44,14 +47,17 @@ def pressure_increasing_test(inp):
     return flags
 
 
-@add_flag_metadata(standard_name="speed_test_quality_flag",
-                   long_name="Speed Test Quality Flag")
-def speed_test(lon: Sequence[N],
-               lat: Sequence[N],
-               tinp: Sequence[N],
-               suspect_threshold: float,
-               fail_threshold: float,
-               ) -> np.ma.core.MaskedArray:
+@add_flag_metadata(
+    standard_name="speed_test_quality_flag",
+    long_name="Speed Test Quality Flag",
+)
+def speed_test(
+    lon: Sequence[N],
+    lat: Sequence[N],
+    tinp: Sequence[N],
+    suspect_threshold: float,
+    fail_threshold: float,
+) -> np.ma.core.MaskedArray:
     """Checks that the calculated speed between two points is within reasonable bounds.
 
     This test calculates a speed between subsequent points by
@@ -121,7 +127,9 @@ def speed_test(lon: Sequence[N],
 
     # calculate speed in m/s
     speed = np.ma.zeros(tinp.size, dtype="float")
-    speed[1:] = np.abs(dist[1:] / np.diff(tinp).astype("timedelta64[s]").astype(float))
+    speed[1:] = np.abs(
+        dist[1:] / np.diff(tinp).astype("timedelta64[s]").astype(float),
+    )
 
     with np.errstate(invalid="ignore"):
         flag_arr[speed > suspect_threshold] = QartodFlags.SUSPECT

ioos_qc/axds.py

@@ -1,5 +1,6 @@
 #!/usr/bin/env python
 """Tests based on the IOOS QARTOD manuals."""
+
 import logging
 from collections import namedtuple
 from typing import Sequence, Tuple
@@ -17,14 +18,17 @@
 span = namedtuple("Span", "minv maxv")
 
 
-@add_flag_metadata(standard_name="gross_range_test_quality_flag",
-                   long_name="Gross Range Test Quality Flag")
-def valid_range_test(inp : Sequence[any],
-                     valid_span : Tuple[any, any],
-                     dtype : np.dtype = None,
-                     start_inclusive : bool = True,
-                     end_inclusive : bool = False,
-                     ) -> np.ma.core.MaskedArray:
+@add_flag_metadata(
+    standard_name="gross_range_test_quality_flag",
+    long_name="Gross Range Test Quality Flag",
+)
+def valid_range_test(
+    inp: Sequence[any],
+    valid_span: Tuple[any, any],
+    dtype: np.dtype = None,
+    start_inclusive: bool = True,
+    end_inclusive: bool = False,
+) -> np.ma.core.MaskedArray:
     """Checks that values are within a min/max range. This is not unlike a `qartod.gross_range_test`
     with fail and suspect bounds being equal, except that here we specify the inclusive range that
     should pass instead of the exclusive bounds which should fail. This also supports datetime-like
@@ -60,14 +64,20 @@ def valid_range_test(inp : Sequence[any],
     # 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
     original_shape = inp.shape
 
     if dtype is None:
-        L.warning("Trying to guess data input type, try specifying the dtype parameter")
+        L.warning(
+            "Trying to guess data input type, try specifying the dtype parameter",
+        )
         # Try to figure out the dtype so masked values can be calculated
         try:
             # Try datetime-like objects
@@ -77,12 +87,15 @@ def valid_range_test(inp : Sequence[any],
             try:
                 # Try floating point numbers
                 inp = np.ma.masked_invalid(np.array(inp).astype(np.floating))
-                valid_span = np.ma.masked_invalid(np.array(valid_span).astype(np.floating))
+                valid_span = np.ma.masked_invalid(
+                    np.array(valid_span).astype(np.floating),
+                )
             except BaseException:
                 # Well, we tried.
                 msg = "Could not determine the type of input, try using the dtype parameter"
                 raise ValueError(
-                    msg)
+                    msg,
+                )
     else:
         inp = np.ma.masked_invalid(np.array(inp, dtype=dtype))
         valid_span = np.ma.masked_invalid(np.array(valid_span, dtype=dtype))