diff --git a/lang/fr/gklearn/kernels/path_up_to_h.py b/lang/fr/gklearn/kernels/path_up_to_h.py index 1c8b5e2..d8cc387 100644 --- a/lang/fr/gklearn/kernels/path_up_to_h.py +++ b/lang/fr/gklearn/kernels/path_up_to_h.py @@ -24,7 +24,7 @@ from gklearn.kernels import GraphKernel from gklearn.utils import Trie -class PathUpToH(GraphKernel): # @todo: add function for k_func == None +class PathUpToH(GraphKernel): # @todo: add function for k_func is None def __init__(self, **kwargs): GraphKernel.__init__(self) @@ -43,7 +43,7 @@ class PathUpToH(GraphKernel): # @todo: add function for k_func == None itr_kernel = combinations_with_replacement(range(0, len(self._graphs)), 2) if self._verbose >= 2: iterator_ps = tqdm(range(0, len(self._graphs)), desc='getting paths', file=sys.stdout) - iterator_kernel = tqdm(itr_kernel, desc='calculating kernels', file=sys.stdout) + iterator_kernel = tqdm(itr_kernel, desc='Computing kernels', file=sys.stdout) else: iterator_ps = range(0, len(self._graphs)) iterator_kernel = itr_kernel @@ -69,7 +69,7 @@ class PathUpToH(GraphKernel): # @todo: add function for k_func == None def _compute_gm_imap_unordered(self): self.__add_dummy_labels(self._graphs) - # get all paths of all graphs before calculating kernels to save time, + # get all paths of all graphs before computing kernels to save time, # but this may cost a lot of memory for large datasets. pool = Pool(self._n_jobs) itr = zip(self._graphs, range(0, len(self._graphs))) @@ -123,7 +123,7 @@ class PathUpToH(GraphKernel): # @todo: add function for k_func == None if self._verbose >= 2: iterator_ps = tqdm(g_list, desc='getting paths', file=sys.stdout) - iterator_kernel = tqdm(range(len(g_list)), desc='calculating kernels', file=sys.stdout) + iterator_kernel = tqdm(range(len(g_list)), desc='Computing kernels', file=sys.stdout) else: iterator_ps = g_list iterator_kernel = range(len(g_list)) @@ -149,7 +149,7 @@ class PathUpToH(GraphKernel): # @todo: add function for k_func == None def _compute_kernel_list_imap_unordered(self, g1, g_list): self.__add_dummy_labels(g_list + [g1]) - # get all paths of all graphs before calculating kernels to save time, + # get all paths of all graphs before computing kernels to save time, # but this may cost a lot of memory for large datasets. pool = Pool(self._n_jobs) itr = zip(g_list, range(0, len(g_list))) @@ -190,7 +190,7 @@ class PathUpToH(GraphKernel): # @todo: add function for k_func == None itr = range(len(g_list)) len_itr = len(g_list) parallel_me(do_fun, func_assign, kernel_list, itr, len_itr=len_itr, - init_worker=init_worker, glbv=(paths_g1, paths_g_list), method='imap_unordered', n_jobs=self._n_jobs, itr_desc='calculating kernels', verbose=self._verbose) + init_worker=init_worker, glbv=(paths_g1, paths_g_list), method='imap_unordered', n_jobs=self._n_jobs, itr_desc='Computing kernels', verbose=self._verbose) return kernel_list @@ -218,7 +218,7 @@ class PathUpToH(GraphKernel): # @todo: add function for k_func == None def __kernel_do_trie(self, trie1, trie2): - """Calculate path graph kernels up to depth d between 2 graphs using trie. + """Compute path graph kernels up to depth d between 2 graphs using trie. Parameters ---------- @@ -335,7 +335,7 @@ class PathUpToH(GraphKernel): # @todo: add function for k_func == None def __kernel_do_naive(self, paths1, paths2): - """Calculate path graph kernels up to depth d between 2 graphs naively. + """Compute path graph kernels up to depth d between 2 graphs naively. Parameters ----------