Bump zipp from 2.2.0 to 3.1.0

Bumps zipp from 2.2.0 to 3.1.0.

Changelog

Sourced from zipp's changelog.

v3.1.0

#47: .open now raises FileNotFoundError and IsADirectoryError when appropriate.

v3.0.0

#44: Merge with v1.2.0.

v1.2.0

#44: zipp.Path.open() now supports a compatible signature as pathlib.Path.open(), accepting text (default) or binary modes and soliciting keyword parameters passed through to io.TextIOWrapper (encoding, newline, etc). The stream is opened in text-mode by default now. open no longer accepts pwd as a positional argument and does not accept the force_zip64 parameter at all. This change is a backward-incompatible change for that single function.

v2.2.1

#43: Merge with v1.1.1.

v1.1.1

#43: Restored performance of implicit dir computation.

Commits

• ec6ff0f Merge pull request #47 from jaraco/feature/exceptions
• 200f0dd Update changelog. Ref #47.
• ffee568 Raise more appropriate exceptions when 'open' is invoked on missing items or ...
• bf4a22f Add tests capturing expectation about specific Exceptions when opening direct...
• 5a06e14 Add test capturing expectation that write works and can be binary or text.
• 19599b7 Rely on dict on Python 3.7 and later where ordering is guaranteed. Performanc...
• 3d17ee5 Rely on Python syntax for pwd keyword argument.
• d2ad6e0 Remove unused import
• bacb253 Update changelog. Ref #44.
• cf0648f Merge tag 'v1.2.0'
• Additional commits viewable in compare view

saqc/funcs/functions.py

@@ -18,12 +18,10 @@ from dios import DictOfSeries
 from typing import Any
 
 
-def _dslIsFlagged(flagger, var, flag=None, comparator=None):
+def _dslIsFlagged(flagger, var, flag=None, comparator=">="):
     """
     helper function for `flagGeneric`
     """
-    if comparator is None:
-        return flagger.isFlagged(var.name, flag=flag)
     return flagger.isFlagged(var.name, flag=flag, comparator=comparator)
 
 
@@ -441,13 +439,25 @@ range_dict.keys()
 
 @register
 def flagCrossScoring(data, field, flagger, fields, thresh, cross_stat=np.median, **kwargs):
-    val_frame = data.loc[data.index_of("shared")].to_df()
-    try:
-        stat = getattr(val_frame, cross_stat.__name__)(axis=1)
-    except AttributeError:
-        stat = val_frame.aggregate(cross_stat, axis=1)
-    diff_scores = val_frame.subtract(stat, axis=0).abs()
-    diff_scores = diff_scores > thresh
+    df = data[fields].loc[data[fields].index_of('shared')].to_df()
+
+    if isinstance(cross_stat, str):
+        if cross_stat == 'modZscore':
+            MAD_series = df.subtract(df.median(axis=1), axis=0).abs().median(axis=1)
+            diff_scores = ((0.6745 * (df.subtract(df.median(axis=1), axis=0))).divide(MAD_series, axis=0)).abs()
+        elif cross_stat == 'Zscore':
+            diff_scores = (df.subtract(df.mean(axis=1), axis=0)).divide(df.std(axis=1), axis=0).abs()
+        else:
+            raise ValueError(cross_stat)
+    else:
+        try:
+            stat = getattr(df, cross_stat.__name__)(axis=1)
+        except AttributeError:
+            stat = df.aggregate(cross_stat, axis=1)
+        diff_scores = df.subtract(stat, axis=0).abs()
+
+    mask = diff_scores > thresh
     for var in fields:
-        flagger = flagger.setFlags(var, diff_scores[var].values, **kwargs)
+        flagger = flagger.setFlags(var, mask[var], **kwargs)
+
     return data, flagger