make DmpFlagger run

dsl/evaluator.py

@@ -119,10 +119,6 @@ def evalExpression(expr: str, flagger: BaseFlagger,
         else:
             raise TypeError(node)
 
-    if not (data.columns == flags.columns).all():
-        raise TypeError(
-            "arguments 'data' and 'flags' need the same column names")
-
     FUNCTIONS = initFunctionNamespace(nodata, flagger)
     namespace = {**namespace,
                  **{"data": data, "flags": flags, "this": field}}

flagger/dmpflagger.py

@@ -26,18 +26,17 @@ class DmpFlagger(BaseFlagger):
     def emptyFlags(self, data, value="NIL", **kwargs):
         columns = data.columns if isinstance(data, pd.DataFrame) else [data.name]
         columns = pd.MultiIndex.from_product([columns, self.flag_fields])
-        return pd.DataFrame(data=value,
-                            columns=columns, index=data.index)
+        return pd.DataFrame(data=value, columns=columns, index=data.index)
 
     def setFlag(self, flags, flag=Flags.BAD, cause="NIL", comment="NIL", **kwargs):
         self._isFlag(flag)
         for field, f in zip(self.flag_fields, [flag, cause, comment]):
-            flags.loc[:, (slice(None), field)] = f
+            flags.loc[:, field] = f
         return flags
 
     def isFlagged(self, flags, flag=None):
         self._isFlag(flag)
-        flagcol = flags.loc[:, (slice(None), FlagFields.FLAG)].squeeze()
+        flagcol = flags.loc[:, FlagFields.FLAG].squeeze()
         return super().isFlagged(flagcol, flag)
 
     def _isFlag(self, flag):

funcs/functions.py

@@ -38,7 +38,10 @@ def flagGeneric(data, flags, field, flagger, nodata=np.nan, **flag_params):
     to_flag = result.filled(True)
 
     fchunk = flagger.setFlag(flags=flags.loc[to_flag, field], **flag_params)
-    flags.loc[to_flag, field] = fchunk
+
+    # .values transform the data to NumPy array, so the assignment
+    # can work for single- and multi- indexed data.
+    flags.loc[to_flag, field] = fchunk.values
 
     return data, flags