style: linting

popmon/analysis/functions.py

@@ -59,11 +59,13 @@ def pull(row, suffix_mean="_mean", suffix_std="_std", cols=None):
     x = {
         m: np.nan
         if (
-            any(r not in rdict or pd.isnull(rdict[r]) for r in [m, m + suffix_mean, m + suffix_std])
+            any(
+                r not in rdict or pd.isnull(rdict[r])
+                for r in [m, m + suffix_mean, m + suffix_std]
+            )
             or rdict[m + suffix_std] == 0.0
         )
-        else
-        (rdict[m] - rdict[m + suffix_mean]) / rdict[m + suffix_std]
+        else (rdict[m] - rdict[m + suffix_mean]) / rdict[m + suffix_std]
         for m in cols
     }
 
@@ -408,7 +410,7 @@ def normalized_hist_mean_cov(x, hist_name=""):
     o = {
         hist_name + "_mean": None,
         hist_name + "_cov": None,
-        hist_name + "_binning": None
+        hist_name + "_binning": None,
     }
 
     # basic checks
@@ -463,7 +465,7 @@ def relative_chi_squared(
         "chi2": np.nan,
         "naive_pvalue": np.nan,
         "naive_zscore": np.nan,
-        "max_res": np.nan
+        "max_res": np.nan,
     }
 
     required = [

popmon/analysis/hist_numpy.py

@@ -287,20 +287,17 @@ def get_consistent_numpy_entries(hist_list, get_bin_labels=False):
 
     # collect list of consistent bin_entries
     if all_num:
-        kwargs = {'xvalues': labels}
+        kwargs = {"xvalues": labels}
     else:
         # PATCH: deal with boolean labels, which get bin_labels() returns as strings
         cat_labels = labels
         props = get_hist_props(hist_list[0])
         if props["is_bool"]:
             cat_labels = [lab == "True" for lab in cat_labels]
 
-        kwargs = {'labels': cat_labels}
+        kwargs = {"labels": cat_labels}
 
-    entries_list = [
-        hist.bin_entries(**kwargs)
-        for hist in hist_list
-    ]
+    entries_list = [hist.bin_entries(**kwargs) for hist in hist_list]
 
     if get_bin_labels:
         return entries_list, labels

popmon/config.py

@@ -17,7 +17,6 @@
 # IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN
 # CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
 
-import multiprocessing
 from fnmatch import fnmatch
 
 from popmon.analysis.comparison.comparisons import Comparisons

popmon/hist/hist_utils.py

@@ -22,14 +22,14 @@
 import histogrammar.specialized
 import numpy as np
 import pandas as pd
-from histogrammar.util import get_hist_props
 from histogrammar.specialized import (
     CategorizeHistogramMethods,
     HistogramMethods,
     SparselyHistogramMethods,
+    SparselyTwoDimensionallyHistogramMethods,
     TwoDimensionallyHistogramMethods,
-    SparselyTwoDimensionallyHistogramMethods
 )
+from histogrammar.util import get_hist_props
 
 COMMON_HIST_TYPES = (
     histogrammar.Categorize,

popmon/stitching/hist_stitcher.py

@@ -281,8 +281,8 @@ def _find_max_time_bin_index(self, hists_basis, features_basis, time_axis):
         hist_list = list(hists_basis.values())
 
         all_sparse = all(isinstance(h, hg.SparselyBin) for h in hist_list)
-        all_cat = (
-            not all_sparse and all(isinstance(h, hg.Categorize) for h in hist_list)
+        all_cat = not all_sparse and all(
+            isinstance(h, hg.Categorize) for h in hist_list
         )
 
         max_time_bin_idx = None