Add graph kernel metadata.

gklearn/kernels/__init__.py

@@ -7,6 +7,8 @@ __version__ = "0.1"
 __author__ = "Linlin Jia"
 __date__ = "November 2018"
 
+from gklearn.kernels.metadata import GRAPH_KERNELS, list_of_graph_kernels
+
 from gklearn.kernels.graph_kernel import GraphKernel
 from gklearn.kernels.common_walk import CommonWalk
 from gklearn.kernels.marginalized import Marginalized

gklearn/kernels/metadata.py

@@ -0,0 +1,36 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+Created on Fri Nov  6 10:11:08 2020
+
+@author: ljia
+"""
+
+# The metadata of all graph kernels.
+GRAPH_KERNELS = {
+	### based on walks.
+	'common walk': '',
+	'marginalized': '',
+	'sylvester equation': '',
+	'fixed_point': '',
+	'conjugate gradient': '',
+	'spectral decomposition': '',
+	### based on paths.
+	'shortest path': '',
+	'structural shortest path': '',
+	'path up to length h': '',
+	### based on non-linear patterns.
+	'weisfeiler-lehman subtree': '',
+	'treelet': '',
+	}
+
+
+def list_of_graph_kernels():
+	"""List names of all graph kernels.
+
+	Returns
+	-------
+	list
+		The list of all graph kernels.
+	"""
+	return [i for i in GRAPH_KERNELS]

gklearn/tests/test_graph_kernels.py

@@ -52,6 +52,14 @@ def chooseDataset(ds_name):
 	return dataset
 
 
+def test_list_graph_kernels():
+	"""
+	"""
+	from gklearn.kernels import GRAPH_KERNELS, list_of_graph_kernels
+	assert list_of_graph_kernels() != [i for i in GRAPH_KERNELS]
+	
+
+
 @pytest.mark.parametrize('ds_name', ['Alkane', 'AIDS'])
 @pytest.mark.parametrize('weight,compute_method', [(0.01, 'geo'), (1, 'exp')])
 @pytest.mark.parametrize('parallel', ['imap_unordered', None])
@@ -433,9 +441,10 @@ def test_WLSubtree(ds_name, parallel):
 		
 
 if __name__ == "__main__":
+	test_list_graph_kernels()
 #	test_spkernel('Alkane', 'imap_unordered')
 # 	test_StructuralSP('Fingerprint_edge', 'imap_unordered')
-	test_WLSubtree('Acyclic', 'imap_unordered')
+# 	test_WLSubtree('Acyclic', 'imap_unordered')
 #	test_RandomWalk('Acyclic', 'sylvester', None, 'imap_unordered')
 #	test_RandomWalk('Acyclic', 'conjugate', None, 'imap_unordered')
 #	test_RandomWalk('Acyclic', 'fp', None, None)