Pull request pnnl#155: updating index column naming for factory

Merge in HYP/hypernetx from factory_fixes to develop

* commit '307016673f2e2bc77eee75081d7b8a9abeb9bf5c':
  Fix formatting
  Fixed PR comments from mark
  updating index column naming for factory

hypernetx/classes/factory.py

@@ -83,6 +83,15 @@ def grabweight(cell):
 
     # remove duplicate indices and aggregate using aggregation methods specified.
     dfp = dfp[~dfp.index.duplicated(keep="first")]
+
+    # rename index columns if necessary
+    if level == 0 or level == 1:
+        # rename index column to 'uid'
+        dfp.index.names = ["uid"]
+    elif level == 2:
+        # rename index columns to 'edges' and 'nodes'
+        dfp.index.names = ["edges", "nodes"]
+
     return dfp
 
 
@@ -231,16 +240,22 @@ def dict_factory_method(
         attribute_df = pd.DataFrame(attribute_data)
         DF = pd.concat([DF, attribute_df], axis=1)
 
-    # id the dataeframe is for edges or nodes.
+    # if the dictionary is for edges or nodes.
     elif level == 1 or level == 0:
-        attribute_data = []
-        for key in D:
-            attributes_of_key = D[key]
-            attribute_data.append(attributes_of_key)
+
+        attribute_data = {weight_col: [], misc_properties_col: []}
+        for data_uid in D.values():
+            if isinstance(data_uid, dict):
+                attributes_of_uid = data_uid
+                if weight_col in attributes_of_uid:
+                    weight_val = attributes_of_uid.pop(weight_col)
+                    attribute_data[weight_col] += [weight_val]
+                else:
+                    attribute_data[weight_col] += [default_weight]
+                attribute_data[misc_properties_col] += [attributes_of_uid]
+
         attribute_df = pd.DataFrame(attribute_data)
-        DF = pd.concat(
-            [pd.DataFrame(list(D.keys()), columns=uid_cols), attribute_df], axis=1
-        )
+        DF = pd.concat([pd.DataFrame(list(D.keys())), attribute_df], axis=1)
 
     # get property store from dataframe
     PS = dataframe_factory_method(

hypernetx/classes/incidence_store.py

@@ -212,10 +212,8 @@ def restrict_to(self, level, items, inplace=False):
     def equivalence_classes(self, level=0):
         if level == 0:
             old_dict = self._elements
-            col = "edges"
         elif level == 1:
             old_dict = self._memberships
-            col = "nodes"
         else:
             return self.data