Adding new methods and the consensual backbone

Adding new methods and the consensual backbone

netbone/filters.py

@@ -12,7 +12,7 @@ def boolean_filter(backbone, narrate=True, value=[]):
             data = nx.to_pandas_edgelist(data)
         if narrate:
             backbone.narrate()
-        return nx.from_pandas_edgelist(data[data[column] == True], edge_attr=edge_properties(data))
+        return nx.from_pandas_edgelist(data[data[column]], edge_attr=edge_properties(data))
     print("The accepted filters for " + backbone.method_name + " are: " + ', '.join(
         [fun.__name__ for fun in backbone.compatible_filters()]))
 
@@ -21,19 +21,30 @@ def threshold_filter(backbone, value, narrate=True, secondary_property='weight',
                      **kwargs):
     data = backbone.to_dataframe()
     property_name = backbone.property_name
-    ascending = backbone.ascending
+    filter_by = [property_name]
+    ascending = [backbone.ascending]
+
+    if backbone.filter_on == 'Edges':
+        filter_by.append(secondary_property)
+        ascending.append(secondary_property_ascending)
 
     if threshold_filter in backbone.compatible_filters():
-        data = data.sort_values(by=[property_name, secondary_property],
-                                ascending=[ascending, secondary_property_ascending])
+        data = data.sort_values(by=filter_by,
+                                ascending=ascending)
 
         if narrate:
             backbone.narrate()
 
-        if ascending:
-            return nx.from_pandas_edgelist(data[data[property_name] < value], edge_attr=edge_properties(data))
+        if backbone.ascending:
+            data = data[data[property_name] < value]
+            if backbone.filter_on == 'Edges':
+                return nx.from_pandas_edgelist(data, edge_attr=edge_properties(data))
+            return backbone.graph.subgraph(list(data.index)).copy()
         else:
-            return nx.from_pandas_edgelist(data[data[property_name] > value], edge_attr=edge_properties(data))
+            data = data[data[property_name] > value]
+            if backbone.filter_on == 'Edges':
+                return nx.from_pandas_edgelist(data, edge_attr=edge_properties(data))
+            return backbone.graph.subgraph(list(data.index)).copy()
 
     print("The accepted filters for " + backbone.method_name + " are: " + ', '.join(
         [fun.__name__ for fun in backbone.compatible_filters()]))
@@ -45,7 +56,6 @@ def fraction_filter(backbone, value, narrate=True, secondary_property='weight',
     filter_by = [backbone.property_name]
     ascending = [backbone.ascending]
 
-
     if backbone.filter_on == 'Edges':
         filter_by.append(secondary_property)
         ascending.append(secondary_property_ascending)
@@ -60,9 +70,8 @@ def fraction_filter(backbone, value, narrate=True, secondary_property='weight',
             value = math.ceil(value * len(data))
             return nx.from_pandas_edgelist(data[:value], edge_attr=edge_properties(data))
         else:
-            b = backbone.graph.copy()
             value = math.ceil(value * len(backbone.graph))
-            return b.subgraph(list(data[:value].index))
+            return backbone.graph.subgraph(list(data[:value].index)).copy()
 
     print("The accepted filters for " + backbone.method_name + " are: " + ', '.join(
         [fun.__name__ for fun in backbone.compatible_filters()]))