DM-23173: Update W504 to W503 and fix flake8 warnings

python/lsst/ap/association/association.py

@@ -173,8 +173,8 @@ def check_dia_source_radec(self, dia_sources):
             DataFrame of DiaSources trimmed of all entries with NaN values for
             RA/DEC.
         """
-        nan_mask = (dia_sources.loc[:, "ra"].isnull() |
-                    dia_sources.loc[:, "decl"].isnull())
+        nan_mask = (dia_sources.loc[:, "ra"].isnull()
+                    | dia_sources.loc[:, "decl"].isnull())
         if np.any(nan_mask):
             nan_idxs = np.argwhere(nan_mask.to_numpy()).flatten()
             for nan_idx in nan_idxs:

python/lsst/ap/association/diaCalculation.py

@@ -319,8 +319,8 @@ def run(self, diaObjectCat, diaSourceCat, updatedDiaObjectIds, filterName):
                 ["diaObjectId", "filterName", "diaSourceId"],
                 inplace=True,
                 drop=False)
-        elif (diaSourceCat.index.names !=
-              ["diaObjectId", "filterName", "diaSourceId"]):
+        elif (diaSourceCat.index.names
+              != ["diaObjectId", "filterName", "diaSourceId"]):
             self.log.warn(
                 "Input diaSourceCat is indexed on column(s) incompatible with "
                 "this task. Should be indexed on 'multi-index, "

python/lsst/ap/association/diaCalculationPlugins.py

@@ -304,8 +304,8 @@ def _weightedMean(df):
             tmpDf = df[~np.logical_or(np.isnan(df["psFlux"]),
                                       np.isnan(df["psFluxErr"]))]
             tot_weight = np.nansum(1 / tmpDf["psFluxErr"] ** 2)
-            fluxMean = np.nansum(tmpDf["psFlux"] /
-                                 tmpDf["psFluxErr"] ** 2)
+            fluxMean = np.nansum(tmpDf["psFlux"]
+                                 / tmpDf["psFluxErr"] ** 2)
             fluxMean /= tot_weight
             fluxMeanErr = np.sqrt(1 / tot_weight)
             nFluxData = len(tmpDf)
@@ -486,8 +486,8 @@ def calculate(self,
         meanName = "{}PSFluxMean".format(filterName)
 
         def _chi2(df):
-            delta = (df["psFlux"] -
-                     diaObjects.at[df.diaObjectId.iat[0], meanName])
+            delta = (df["psFlux"]
+                     - diaObjects.at[df.diaObjectId.iat[0], meanName])
             return np.nansum((delta / df["psFluxErr"]) ** 2)
 
         diaObjects.loc[:, "{}PSFluxChi2".format(filterName)] = \
@@ -1029,8 +1029,8 @@ def _meanFlux(df):
             tmpDf = df[~np.logical_or(np.isnan(df["totFlux"]),
                                       np.isnan(df["totFluxErr"]))]
             tot_weight = np.nansum(1 / tmpDf["totFluxErr"] ** 2)
-            fluxMean = np.nansum(tmpDf["totFlux"] /
-                                 tmpDf["totFluxErr"] ** 2)
+            fluxMean = np.nansum(tmpDf["totFlux"]
+                                 / tmpDf["totFluxErr"] ** 2)
             fluxMean /= tot_weight
             fluxMeanErr = np.sqrt(1 / tot_weight)
 

setup.cfg

@@ -1,6 +1,6 @@
 [flake8]
 max-line-length = 110
-ignore = E133, E226, E228, N802, N803, N806, N812, N815, N816, W504
+ignore = E133, E226, E228, N802, N803, N806, N812, N815, N816, W503
 exclude =
   bin,
   doc,
@@ -11,4 +11,4 @@ exclude =
 
 [tool:pytest]
 addopts = --flake8
-flake8-ignore = E133 E226 E228 N802 N803 N806 N812 N815 N816 W504
+flake8-ignore = E133 E226 E228 N802 N803 N806 N812 N815 N816 W503

tests/test_association_task.py

@@ -378,16 +378,16 @@ def _set_source_values(self, dia_source, flux, fluxErr, filterName,
         dia_source["midPointTai"] = midPointTai
         dia_source["psFlux"] = flux / self.flux0
         dia_source["psFluxErr"] = np.sqrt(
-            (fluxErr / self.flux0) ** 2 +
-            (flux * self.flux0_err / self.flux0 ** 2) ** 2)
+            (fluxErr / self.flux0) ** 2
+            + (flux * self.flux0_err / self.flux0 ** 2) ** 2)
         dia_source["apFlux"] = flux / self.flux0
         dia_source["apFluxErr"] = np.sqrt(
-            (fluxErr / self.flux0) ** 2 +
-            (flux * self.flux0_err / self.flux0 ** 2) ** 2)
+            (fluxErr / self.flux0) ** 2
+            + (flux * self.flux0_err / self.flux0 ** 2) ** 2)
         dia_source["totFlux"] = flux / self.flux0
         dia_source["totFluxErr"] = np.sqrt(
-            (fluxErr / self.flux0) ** 2 +
-            (flux * self.flux0_err / self.flux0 ** 2) ** 2)
+            (fluxErr / self.flux0) ** 2
+            + (flux * self.flux0_err / self.flux0 ** 2) ** 2)
         dia_source["filterName"] = filterName
         dia_source["filterId"] = filterId
         dia_source["x"] = 0.

tests/test_dia_calculation.py

@@ -98,9 +98,9 @@ def calculate(self,
                   filterName,
                   **kwargs):
         diaObjects.at[diaObjectId, "%sChiFlux" % filterName] = np.sum(
-            ((filterDiaSources["psFlux"] -
-              diaObjects.at[diaObjectId, "%sMeanFlux" % filterName]) /
-             filterDiaSources["psFluxErr"]) ** 2)
+            ((filterDiaSources["psFlux"]
+              - diaObjects.at[diaObjectId, "%sMeanFlux" % filterName])
+             / filterDiaSources["psFluxErr"]) ** 2)
 
 
 @register("testCollidingDiaPlugin")

tests/test_dia_calculation_plugins.py

@@ -490,9 +490,9 @@ def testCalculate(self):
         run_multi_plugin(diaObjects, diaSources, "u", plug)
         self.assertAlmostEqual(
             diaObjects.loc[objId, "uPSFluxChi2"],
-            np.nansum(((diaSources["psFlux"] -
-                        np.nanmean(diaSources["psFlux"])) /
-                       diaSources["psFluxErr"]) ** 2))
+            np.nansum(((diaSources["psFlux"]
+                        - np.nanmean(diaSources["psFlux"]))
+                       / diaSources["psFluxErr"]) ** 2))
 
         # Test expected chi^2 value with a nan value set.
         fluxes[4] = np.nan
@@ -507,9 +507,9 @@ def testCalculate(self):
         run_multi_plugin(diaObjects, diaSources, "r", plug)
         self.assertAlmostEqual(
             diaObjects.loc[objId, "rPSFluxChi2"],
-            np.nansum(((diaSources["psFlux"] -
-                        np.nanmean(diaSources["psFlux"])) /
-                       diaSources["psFluxErr"]) ** 2))
+            np.nansum(((diaSources["psFlux"]
+                        - np.nanmean(diaSources["psFlux"]))
+                       / diaSources["psFluxErr"]) ** 2))
 
 
 class TestMadDiaPsFlux(unittest.TestCase):