Pull request #169: Additems

Merge in HYP/hypernetx from additems to develop

* commit '9222850657767bde88a0846dfe4c8f8cd2288a39':
  Minor cleanup
  added import for deepcopy
  updated copy in PropertyStore to deep copy misc_properties
  updated construct from stores to return inplace or deep copy
  restricting todataframe to only return on objects actually in the hypergraph

hypernetx/classes/hyp_view.py

@@ -57,12 +57,6 @@ def __init__(self, incidence_store, level, property_store=None):
         elif level == 2:
             self._items = self._incidence_store
 
-        # self._properties = PropertyStore()
-        ### if no properties and level 0 or 1,
-        ### create property store that
-        ### returns weight 1 on every call for a weight
-        ### and empty properties otherwise.
-
     @property
     def items(self):
         return set(self._items)
@@ -79,6 +73,10 @@ def incidence_store(self):
     def property_store(self):
         return self._property_store
 
+    @property
+    def default_weight(self):
+        return self._property_store._default_weight
+
     @property
     def to_dataframe(self):
         """
@@ -90,7 +88,9 @@ def to_dataframe(self):
         out: pd.DataFrame
         """
         # Create a properties dataframe of non-user-defined items with default values
+
         df = self.properties.copy(deep=True)
+
         ### deep copy dictionaries in the misc_properties column
         temp = [deepcopy(d) for d in df.misc_properties.values]
         df.misc_properties = temp
@@ -104,7 +104,7 @@ def to_dataframe(self):
         )
 
         # Combine user-defined and non-user-defined properties into one dataframe
-        return pd.concat([df, non_user_defined_properties])
+        return pd.concat([df, non_user_defined_properties]).loc[list(self.items)]
 
     @property  ### will remove this later
     def dataframe(self):

hypernetx/classes/hypergraph.py

@@ -631,21 +631,16 @@ def clone(self, name=None):
         -------
         : Hypergraph
         """
-        df = self.incidences.to_dataframe
-        eps = PropertyStore(self.edges.to_dataframe)
-        nps = PropertyStore(self.nodes.to_dataframe)
-        return self._construct_hyp_from_stores(df, edge_ps=eps, node_ps=nps, name=name)
+        return self._construct_hyp_from_stores(
+            self.incidences.to_dataframe, name=f"{self.name}_clone"
+        )
 
     def __eq__(self, other):
         if type(other) is type(self):
-            return (
-                all(n in self.nodes for n in other.nodes)
-                and all(e in self.edges for e in other.edges)
-                and self.incidence_dict == other.incidence_dict
-            )
+            return self.incidences.items == other.incidences.items
         return False
 
-    def rename(self, edges=None, nodes=None, name=None):
+    def rename(self, edges=None, nodes=None, name=None, inplace=True):
         """
         _summary_
 
@@ -675,7 +670,9 @@ def rename(self, edges=None, nodes=None, name=None):
             df = df.rename(index=nodes, level=1)
         eps = PropertyStore(edf)
         nps = PropertyStore(ndf)
-        return self._construct_hyp_from_stores(df, edge_ps=eps, node_ps=nps, name=name)
+        return self._construct_hyp_from_stores(
+            df, edge_ps=eps, node_ps=nps, name=name, inplace=inplace
+        )
 
     def get_cell_properties(self, edge_uid, node_uid, prop_name=None):
         """Get cell properties on a specified edge and node
@@ -1123,23 +1120,32 @@ def bipartite(self, keep_data=False, directed=False):
         return B
 
     def _construct_hyp_from_stores(
-        self, incidence_df, edge_ps=None, node_ps=None, name=None
+        self, incidence_df, edge_ps=None, node_ps=None, name=None, inplace=False
     ):
-
-        h = Hypergraph()
+        if inplace:
+            h = self
+            name = self.name
+        else:
+            h = Hypergraph()
 
         incidence_store = IncidenceStore(
             pd.DataFrame(incidence_df.index.tolist(), columns=["edges", "nodes"])
         )
-        incidence_ps = PropertyStore(incidence_df)
+        incidence_ps = PropertyStore(
+            incidence_df, default_weight=self.incidences.default_weight
+        )
         h._E = HypergraphView(incidence_store, 2, incidence_ps)
 
         if edge_ps is None:
-            edge_ps = self.edges.property_store.copy()
+            edge_ps = PropertyStore(
+                self.edges.to_dataframe, default_weight=self.edges.default_weight
+            )
         h._edges = HypergraphView(incidence_store, 0, edge_ps)
 
         if node_ps is None:
-            node_ps = self.nodes.property_store.copy()
+            node_ps = PropertyStore(
+                self.nodes.to_dataframe, default_weight=self.nodes.default_weight
+            )
         h._nodes = HypergraphView(incidence_store, 1, node_ps)
 
         h._set_default_state()
@@ -1586,7 +1592,7 @@ def restrict_to_edges(self, edges, name=None):
         keys = list(set(self._state_dict["labels"]["edges"]).difference(edges))
         return self._remove(keys, level=0, name=name, inplace=False)
 
-    def add_edge(self, uid, **attr):
+    def add_edge(self, uid, inplace=True, **attr):
         """
         Add a single edge with attributes to edge properties.
         Does not add an incidence to the hypergraph.
@@ -1601,22 +1607,22 @@ def add_edge(self, uid, **attr):
         -------
         Hypergraph
         """
-        return self._add_items_from([(uid, attr)], 0)
+        return self._add_items_from([(uid, attr)], 0, inplace=inplace)
 
-    def add_edges_from(self, edges):
+    def add_edges_from(self, edges, inplace=True):
         """Edges must be a list of uids and/or tuples
         of the form (uid,data) where data is dictionary"""
         newedges = self._process_items(edges)
-        return self._add_items_from(newedges, 0)
+        return self._add_items_from(newedges, 0, inplace=inplace)
 
-    def add_node(self, uid, **attr):
-        return self._add_items_from([(uid, attr)], 1)
+    def add_node(self, uid, inplace=True, **attr):
+        return self._add_items_from([(uid, attr)], 1, inplace=inplace)
 
-    def add_nodes_from(self, nodes):
+    def add_nodes_from(self, nodes, inplace=True):
         """Nodes must be a list of uids and/or tuples
         of the form (uid,data) where data is dictionary"""
         newnodes = self._process_items(nodes)
-        return self._add_items_from(newnodes, 1)
+        return self._add_items_from(newnodes, 1, inplace=inplace)
 
     def _process_items(self, items):
         new_items = list()
@@ -1627,7 +1633,7 @@ def _process_items(self, items):
                 new_items.append(item)
         return new_items
 
-    def add_nodes_to_edges(self, edge_dict):
+    def add_nodes_to_edges(self, edge_dict, inplace=True):
         """
         Parameters
         ----------
@@ -1648,12 +1654,12 @@ def add_nodes_to_edges(self, edge_dict):
             else:
                 for nd in nodes:
                     items.append(((ed, nd), {}))
-        return self._add_items_from(items, 2)
+        return self._add_items_from(items, 2, inplace=inplace)
 
-    def add_incidence(self, edge_id, node_id, **attr):
-        return self._add_items_from([((edge_id, node_id), attr)], 2)
+    def add_incidence(self, edge_id, node_id, inplace=True, **attr):
+        return self._add_items_from([((edge_id, node_id), attr)], 2, inplace=inplace)
 
-    def add_incidences_from(self, incidences):
+    def add_incidences_from(self, incidences, inplace=True):
         """
         Adds incidences to Hypergraph
 
@@ -1675,9 +1681,9 @@ def add_incidences_from(self, incidences):
                 newincidences.append((pr, {}))
             else:
                 newincidences.append(((pr[0], pr[1]), pr[2]))
-        return self._add_items_from(newincidences, 2)
+        return self._add_items_from(newincidences, 2, inplace=inplace)
 
-    def _add_items_from(self, items, level):
+    def _add_items_from(self, items, level, inplace=True):
         """Items must be a list of tuples
         of the form (uid,data) where data is dictionary"""
         df = self.incidences._property_store
@@ -1689,7 +1695,7 @@ def _add_items_from(self, items, level):
             data = item[1]
             hv.set_properties(uid, data)
         return self._construct_hyp_from_stores(
-            df.properties, edge_ps=ep, node_ps=ndp, name=self.name
+            df.properties, edge_ps=ep, node_ps=ndp, name=self.name, inplace=inplace
         )
 
     #### This should follow behavior of restrictions
@@ -1752,7 +1758,7 @@ def _remove(
             ep = self.edges.property_store
             ndp = self.nodes.property_store
         else:
-            df = self.incidences.properties.copy(deep=True)
+            df = self.incidences.to_dataframe
             ep = self.edges.property_store.copy(deep=True)
             ndp = self.nodes.property_store.copy(deep=True)
         if level in [0, 1]:
@@ -1761,15 +1767,9 @@ def _remove(
             hv._data = hv._data.drop(labels=uid_list, errors="ignore")
         else:
             df = df.drop(labels=uid_list, errors="ignore")
-        if inplace:
-            self = self._construct_hyp_from_stores(
-                df, edge_ps=ep, node_ps=ndp, name=self.name
-            )
-            return self
-        else:
-            return self._construct_hyp_from_stores(
-                df, edge_ps=ep, node_ps=ndp, name=name
-            )
+        return self._construct_hyp_from_stores(
+            df, edge_ps=ep, node_ps=ndp, name=self.name, inplace=inplace
+        )
 
     def toplexes(self, return_hyp=False, name=None):
         """

hypernetx/classes/property_store.py

@@ -1,6 +1,7 @@
 from typing import Any
 from collections.abc import Hashable
 from pandas import DataFrame
+from copy import deepcopy
 
 
 UID = "uid"
@@ -41,8 +42,7 @@ def __init__(self, data=None, default_weight=1):
             <edge2uid> | <node1uid>  | 1.0    | {}              | <property value>      | ...
                        | <node3uid>  | 1.0    | {}              | <property value>      | ...
 
-        default_weight: int
-
+        default_weight: int | float
             optional parameter that holds the specified default weight of the weight property
         """
         # If no dataframe is provided, create an empty dataframe
@@ -52,7 +52,7 @@ def __init__(self, data=None, default_weight=1):
         else:
             self._data: DataFrame = data
 
-        self._default_weight: int = default_weight
+        self._default_weight: int | float = default_weight
         self._columns = self._data.columns.tolist()
 
     @property
@@ -255,8 +255,10 @@ def __contains__(self, uid) -> bool:
 
     def copy(self, deep=False):
         data = self._data.copy(deep=deep)
-        w = self._default_weight
-        return PropertyStore(data, default_weight=w)
+        if deep:
+            temp = [deepcopy(d) for d in data.misc_properties.values]
+            data["misc_properties"] = temp
+        return PropertyStore(data, default_weight=self._default_weight)
 
 
 def flatten(my_dict):