From 4b0b9647cea33cbf633a385ab8a17a1d90dd1bc0 Mon Sep 17 00:00:00 2001 From: linlin Date: Mon, 19 Oct 2020 15:28:48 +0200 Subject: [PATCH] New translations shortest_path.py (French) --- lang/fr/gklearn/kernels/shortest_path.py | 66 ++++++++++++++++---------------- 1 file changed, 33 insertions(+), 33 deletions(-) diff --git a/lang/fr/gklearn/kernels/shortest_path.py b/lang/fr/gklearn/kernels/shortest_path.py index b068e6e..794095e 100644 --- a/lang/fr/gklearn/kernels/shortest_path.py +++ b/lang/fr/gklearn/kernels/shortest_path.py @@ -26,11 +26,11 @@ class ShortestPath(GraphKernel): def __init__(self, **kwargs): GraphKernel.__init__(self) - self.__node_labels = kwargs.get('node_labels', []) - self.__node_attrs = kwargs.get('node_attrs', []) - self.__edge_weight = kwargs.get('edge_weight', None) - self.__node_kernels = kwargs.get('node_kernels', None) - self.__ds_infos = kwargs.get('ds_infos', {}) + self._node_labels = kwargs.get('node_labels', []) + self._node_attrs = kwargs.get('node_attrs', []) + self._edge_weight = kwargs.get('edge_weight', None) + self._node_kernels = kwargs.get('node_kernels', None) + self._ds_infos = kwargs.get('ds_infos', {}) def _compute_gm_series(self): @@ -39,7 +39,7 @@ class ShortestPath(GraphKernel): iterator = tqdm(self._graphs, desc='getting sp graphs', file=sys.stdout) else: iterator = self._graphs - self._graphs = [getSPGraph(g, edge_weight=self.__edge_weight) for g in iterator] + self._graphs = [getSPGraph(g, edge_weight=self._edge_weight) for g in iterator] # compute Gram matrix. gram_matrix = np.zeros((len(self._graphs), len(self._graphs))) @@ -51,7 +51,7 @@ class ShortestPath(GraphKernel): else: iterator = itr for i, j in iterator: - kernel = self.__sp_do(self._graphs[i], self._graphs[j]) + kernel = self._sp_do(self._graphs[i], self._graphs[j]) gram_matrix[i][j] = kernel gram_matrix[j][i] = kernel @@ -92,12 +92,12 @@ class ShortestPath(GraphKernel): def _compute_kernel_list_series(self, g1, g_list): # get shortest path graphs of g1 and each graph in g_list. - g1 = getSPGraph(g1, edge_weight=self.__edge_weight) + g1 = getSPGraph(g1, edge_weight=self._edge_weight) if self._verbose >= 2: iterator = tqdm(g_list, desc='getting sp graphs', file=sys.stdout) else: iterator = g_list - g_list = [getSPGraph(g, edge_weight=self.__edge_weight) for g in iterator] + g_list = [getSPGraph(g, edge_weight=self._edge_weight) for g in iterator] # compute kernel list. kernel_list = [None] * len(g_list) @@ -106,7 +106,7 @@ class ShortestPath(GraphKernel): else: iterator = range(len(g_list)) for i in iterator: - kernel = self.__sp_do(g1, g_list[i]) + kernel = self._sp_do(g1, g_list[i]) kernel_list[i] = kernel return kernel_list @@ -114,7 +114,7 @@ class ShortestPath(GraphKernel): def _compute_kernel_list_imap_unordered(self, g1, g_list): # get shortest path graphs of g1 and each graph in g_list. - g1 = getSPGraph(g1, edge_weight=self.__edge_weight) + g1 = getSPGraph(g1, edge_weight=self._edge_weight) pool = Pool(self._n_jobs) get_sp_graphs_fun = self._wrapper_get_sp_graphs itr = zip(g_list, range(0, len(g_list))) @@ -151,55 +151,55 @@ class ShortestPath(GraphKernel): def _wrapper_kernel_list_do(self, itr): - return itr, self.__sp_do(G_g1, G_gl[itr]) + return itr, self._sp_do(G_g1, G_gl[itr]) def _compute_single_kernel_series(self, g1, g2): - g1 = getSPGraph(g1, edge_weight=self.__edge_weight) - g2 = getSPGraph(g2, edge_weight=self.__edge_weight) - kernel = self.__sp_do(g1, g2) + g1 = getSPGraph(g1, edge_weight=self._edge_weight) + g2 = getSPGraph(g2, edge_weight=self._edge_weight) + kernel = self._sp_do(g1, g2) return kernel def _wrapper_get_sp_graphs(self, itr_item): g = itr_item[0] i = itr_item[1] - return i, getSPGraph(g, edge_weight=self.__edge_weight) + return i, getSPGraph(g, edge_weight=self._edge_weight) - def __sp_do(self, g1, g2): + def _sp_do(self, g1, g2): kernel = 0 # compute shortest path matrices first, method borrowed from FCSP. vk_dict = {} # shortest path matrices dict - if len(self.__node_labels) > 0: + if len(self._node_labels) > 0: # node symb and non-synb labeled - if len(self.__node_attrs) > 0: - kn = self.__node_kernels['mix'] + if len(self._node_attrs) > 0: + kn = self._node_kernels['mix'] for n1, n2 in product( g1.nodes(data=True), g2.nodes(data=True)): - n1_labels = [n1[1][nl] for nl in self.__node_labels] - n2_labels = [n2[1][nl] for nl in self.__node_labels] - n1_attrs = [n1[1][na] for na in self.__node_attrs] - n2_attrs = [n2[1][na] for na in self.__node_attrs] + n1_labels = [n1[1][nl] for nl in self._node_labels] + n2_labels = [n2[1][nl] for nl in self._node_labels] + n1_attrs = [n1[1][na] for na in self._node_attrs] + n2_attrs = [n2[1][na] for na in self._node_attrs] vk_dict[(n1[0], n2[0])] = kn(n1_labels, n2_labels, n1_attrs, n2_attrs) # node symb labeled else: - kn = self.__node_kernels['symb'] + kn = self._node_kernels['symb'] for n1 in g1.nodes(data=True): for n2 in g2.nodes(data=True): - n1_labels = [n1[1][nl] for nl in self.__node_labels] - n2_labels = [n2[1][nl] for nl in self.__node_labels] + n1_labels = [n1[1][nl] for nl in self._node_labels] + n2_labels = [n2[1][nl] for nl in self._node_labels] vk_dict[(n1[0], n2[0])] = kn(n1_labels, n2_labels) else: # node non-synb labeled - if len(self.__node_attrs) > 0: - kn = self.__node_kernels['nsymb'] + if len(self._node_attrs) > 0: + kn = self._node_kernels['nsymb'] for n1 in g1.nodes(data=True): for n2 in g2.nodes(data=True): - n1_attrs = [n1[1][na] for na in self.__node_attrs] - n2_attrs = [n2[1][na] for na in self.__node_attrs] + n1_attrs = [n1[1][na] for na in self._node_attrs] + n2_attrs = [n2[1][na] for na in self._node_attrs] vk_dict[(n1[0], n2[0])] = kn(n1_attrs, n2_attrs) # node unlabeled else: @@ -210,7 +210,7 @@ class ShortestPath(GraphKernel): return kernel # compute graph kernels - if self.__ds_infos['directed']: + if self._ds_infos['directed']: for e1, e2 in product(g1.edges(data=True), g2.edges(data=True)): if e1[2]['cost'] == e2[2]['cost']: nk11, nk22 = vk_dict[(e1[0], e2[0])], vk_dict[(e1[1], e2[1])] @@ -261,4 +261,4 @@ class ShortestPath(GraphKernel): def _wrapper_sp_do(self, itr): i = itr[0] j = itr[1] - return i, j, self.__sp_do(G_gs[i], G_gs[j]) \ No newline at end of file + return i, j, self._sp_do(G_gs[i], G_gs[j]) \ No newline at end of file