From b4747fc16b3f959f08115fb3e5d220fa01729717 Mon Sep 17 00:00:00 2001
From: jajupmochi <jajupmochi@gmail.com>
Date: Tue, 7 Apr 2020 16:55:36 +0200
Subject: [PATCH] fix bug "AttributeError("'Graph' object has no attribute
 'node'",)" for new version of NetworkX.

---
 gklearn/kernels/__init__.py                   | 1 +
 gklearn/kernels/graph_kernel.py               | 2 +-
 gklearn/kernels/treeletKernel.py              | 2 +-
 gklearn/kernels/untilHPathKernel.py           | 2 +-
 gklearn/preimage/median_preimage_generator.py | 2 +-
 gklearn/utils/utils.py                        | 2 +-
 6 files changed, 6 insertions(+), 5 deletions(-)

diff --git a/gklearn/kernels/__init__.py b/gklearn/kernels/__init__.py
index 951c04a..73147ba 100644
--- a/gklearn/kernels/__init__.py
+++ b/gklearn/kernels/__init__.py
@@ -9,3 +9,4 @@ __date__ = "November 2018"
 
 from gklearn.kernels.graph_kernel import GraphKernel
 from gklearn.kernels.structural_sp import StructuralSP
+from gklearn.kernels.shortest_path import ShortestPath
diff --git a/gklearn/kernels/graph_kernel.py b/gklearn/kernels/graph_kernel.py
index e703981..6f667e1 100644
--- a/gklearn/kernels/graph_kernel.py
+++ b/gklearn/kernels/graph_kernel.py
@@ -44,7 +44,7 @@ class GraphKernel(object):
 			
 		elif len(graphs) == 2:
 			if self.is_graph(graphs[0]) and self.is_graph(graphs[1]):
-				kernel = self.__compute_single_kernel(graphs[0], graphs[1])
+				kernel = self.__compute_single_kernel(graphs[0].copy(), graphs[1].copy())
 				return kernel, self._run_time
 			elif self.is_graph(graphs[0]) and isinstance(graphs[1], list):
 				g1 = graphs[0].copy()
diff --git a/gklearn/kernels/treeletKernel.py b/gklearn/kernels/treeletKernel.py
index 85fc3c7..51cdd08 100644
--- a/gklearn/kernels/treeletKernel.py
+++ b/gklearn/kernels/treeletKernel.py
@@ -308,7 +308,7 @@ def get_canonkeys(G, node_label, edge_label, labeled, is_directed):
         for i in range(1, 6): # for i in range(1, 6):
             treelet = []
             for pattern in patterns[str(i)]:
-                canonlist = list(chain.from_iterable((G.node[node][node_label], \
+                canonlist = list(chain.from_iterable((G.nodes[node][node_label], \
                     G[node][pattern[idx+1]][edge_label]) for idx, node in enumerate(pattern[:-1])))
                 canonlist.append(G.node[pattern[-1]][node_label])
                 canonkey_t = canonlist if canonlist < canonlist[::-1] else canonlist[::-1]
diff --git a/gklearn/kernels/untilHPathKernel.py b/gklearn/kernels/untilHPathKernel.py
index 55649f7..052ea93 100644
--- a/gklearn/kernels/untilHPathKernel.py
+++ b/gklearn/kernels/untilHPathKernel.py
@@ -637,7 +637,7 @@ def paths2labelseqs(plist, G, ds_attrs, node_label, edge_label):
                             (G.node[node][node_label],
                              G[node][path[idx + 1]][edge_label])
                             for idx, node in enumerate(path[:-1]))) +
-                    [G.node[path[-1]][node_label]]) for path in plist
+                    [G.nodes[path[-1]][node_label]]) for path in plist
             ]
             # path_strs = []
             # for path in all_paths:
diff --git a/gklearn/preimage/median_preimage_generator.py b/gklearn/preimage/median_preimage_generator.py
index b10a598..b4f4f80 100644
--- a/gklearn/preimage/median_preimage_generator.py
+++ b/gklearn/preimage/median_preimage_generator.py
@@ -704,7 +704,7 @@ class MedianPreimageGenerator(PreimageGenerator):
 			
 			
 # 	def __clean_graph(self, G, node_labels=[], edge_labels=[], node_attrs=[], edge_attrs=[]):
-	def __clean_graph(self, G):
+	def __clean_graph(self, G): # @todo: this may not be needed when datafile is updated.
 		"""
 		Cleans node and edge labels and attributes of the given graph.
 		"""
diff --git a/gklearn/utils/utils.py b/gklearn/utils/utils.py
index 2a95ea2..d888591 100644
--- a/gklearn/utils/utils.py
+++ b/gklearn/utils/utils.py
@@ -134,7 +134,7 @@ def untotterTransformation(G, node_label, edge_label):
 	gt.add_nodes_from(G.nodes(data=True))
 	for edge in G.edges():
 		gt.add_node(edge)
-		gt.node[edge].update({node_label: G.node[edge[1]][node_label]})
+		gt.nodes[edge].update({node_label: G.node[edge[1]][node_label]})
 		gt.add_edge(edge[0], edge)
 		gt.edges[edge[0], edge].update({
 			edge_label: