diff --git a/lang/fr/gklearn/kernels/treeletKernel.py b/lang/fr/gklearn/kernels/treeletKernel.py index 809a623..14577ff 100644 --- a/lang/fr/gklearn/kernels/treeletKernel.py +++ b/lang/fr/gklearn/kernels/treeletKernel.py @@ -29,15 +29,15 @@ def treeletkernel(*args, n_jobs=None, chunksize=None, verbose=True): - """Calculate treelet graph kernels between graphs. + """Compute treelet graph kernels between graphs. Parameters ---------- Gn : List of NetworkX graph - List of graphs between which the kernels are calculated. + List of graphs between which the kernels are computed. G1, G2 : NetworkX graphs - Two graphs between which the kernel is calculated. + Two graphs between which the kernel is computed. sub_kernel : function The sub-kernel between 2 real number vectors. Each vector counts the @@ -89,7 +89,7 @@ def treeletkernel(*args, # ---- use pool.imap_unordered to parallel and track progress. ---- if parallel == 'imap_unordered': - # get all canonical keys of all graphs before calculating kernels to save + # get all canonical keys of all graphs before computing kernels to save # time, but this may cost a lot of memory for large dataset. pool = Pool(n_jobs) itr = zip(Gn, range(0, len(Gn))) @@ -120,8 +120,8 @@ def treeletkernel(*args, glbv=(canonkeys,), n_jobs=n_jobs, chunksize=chunksize, verbose=verbose) # ---- do not use parallelization. ---- - elif parallel == None: - # get all canonical keys of all graphs before calculating kernels to save + elif parallel is None: + # get all canonical keys of all graphs before computing kernels to save # time, but this may cost a lot of memory for large dataset. canonkeys = [] for g in (tqdm(Gn, desc='getting canonkeys', file=sys.stdout) if verbose else Gn): @@ -148,7 +148,7 @@ def treeletkernel(*args, def _treeletkernel_do(canonkey1, canonkey2, sub_kernel): - """Calculate treelet graph kernel between 2 graphs. + """Compute treelet graph kernel between 2 graphs. Parameters ---------- @@ -210,7 +210,7 @@ def get_canonkeys(G, node_label, edge_label, labeled, is_directed): # n-star patterns patterns['3star'] = [[node] + [neighbor for neighbor in G[node]] for node in G.nodes() if G.degree(node) == 3] - patterns['4star'] = [[node] + [neighbor for neighbor in G[node]] for node in G.nodes() if G.degree(node) == 4] + patterns['4star'] = [[node] + [neighbor for neighbor in G[node]] for node in G.nodes() if G.degree(node) == 4] # @todo: check self loop. patterns['5star'] = [[node] + [neighbor for neighbor in G[node]] for node in G.nodes() if G.degree(node) == 5] # n-star patterns canonkey['6'] = len(patterns['3star'])