| @@ -0,0 +1,86 @@ | |||||
| #!/usr/bin/env python3 | |||||
| # -*- coding: utf-8 -*- | |||||
| """ | |||||
| Created on Wed Aug 19 16:55:17 2020 | |||||
| @author: ljia | |||||
| @references: | |||||
| [1] S Vichy N Vishwanathan, Nicol N Schraudolph, Risi Kondor, and Karsten M Borgwardt. Graph kernels. Journal of Machine Learning Research, 11(Apr):1201–1242, 2010. | |||||
| """ | |||||
| import networkx as nx | |||||
| from gklearn.utils import SpecialLabel | |||||
| from gklearn.kernels import GraphKernel | |||||
| class RandomWalkMeta(GraphKernel): | |||||
| def __init__(self, **kwargs): | |||||
| GraphKernel.__init__(self) | |||||
| self._weight = kwargs.get('weight', 1) | |||||
| self._p = kwargs.get('p', None) | |||||
| self._q = kwargs.get('q', None) | |||||
| self._edge_weight = kwargs.get('edge_weight', None) | |||||
| self._ds_infos = kwargs.get('ds_infos', {}) | |||||
| def _compute_gm_series(self): | |||||
| pass | |||||
| def _compute_gm_imap_unordered(self): | |||||
| pass | |||||
| def _compute_kernel_list_series(self, g1, g_list): | |||||
| pass | |||||
| def _compute_kernel_list_imap_unordered(self, g1, g_list): | |||||
| pass | |||||
| def _compute_single_kernel_series(self, g1, g2): | |||||
| pass | |||||
| def _check_graphs(self, Gn): | |||||
| # remove graphs with no edges, as no walk can be found in their structures, | |||||
| # so the weight matrix between such a graph and itself might be zero. | |||||
| for g in Gn: | |||||
| if nx.number_of_edges(g) == 0: | |||||
| raise Exception('Graphs must contain edges to construct weight matrices.') | |||||
| def _check_edge_weight(self, G0, verbose): | |||||
| eweight = None | |||||
| if self._edge_weight is None: | |||||
| if verbose >= 2: | |||||
| print('\n None edge weight is specified. Set all weight to 1.\n') | |||||
| else: | |||||
| try: | |||||
| some_weight = list(nx.get_edge_attributes(G0, self._edge_weight).values())[0] | |||||
| if isinstance(some_weight, float) or isinstance(some_weight, int): | |||||
| eweight = self._edge_weight | |||||
| else: | |||||
| if verbose >= 2: | |||||
| print('\n Edge weight with name %s is not float or integer. Set all weight to 1.\n' % self._edge_weight) | |||||
| except: | |||||
| if verbose >= 2: | |||||
| print('\n Edge weight with name "%s" is not found in the edge attributes. Set all weight to 1.\n' % self._edge_weight) | |||||
| self._edge_weight = eweight | |||||
| def _add_dummy_labels(self, Gn): | |||||
| if len(self._node_labels) == 0 or (len(self._node_labels) == 1 and self._node_labels[0] == SpecialLabel.DUMMY): | |||||
| for i in range(len(Gn)): | |||||
| nx.set_node_attributes(Gn[i], '0', SpecialLabel.DUMMY) | |||||
| self._node_labels = [SpecialLabel.DUMMY] | |||||
| if len(self._edge_labels) == 0 or (len(self._edge_labels) == 1 and self._edge_labels[0] == SpecialLabel.DUMMY): | |||||
| for i in range(len(Gn)): | |||||
| nx.set_edge_attributes(Gn[i], '0', SpecialLabel.DUMMY) | |||||
| self._edge_labels = [SpecialLabel.DUMMY] | |||||