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New translations untilHPathKernel.py (French)

l10n_v0.2.x
linlin 4 years ago
parent
commit
b6c393ea9f
1 changed files with 17 additions and 17 deletions
  1. +17
    -17
      lang/fr/gklearn/kernels/untilHPathKernel.py

+ 17
- 17
lang/fr/gklearn/kernels/untilHPathKernel.py View File

@@ -34,15 +34,15 @@ def untilhpathkernel(*args,
n_jobs=None, n_jobs=None,
chunksize=None, chunksize=None,
verbose=True): verbose=True):
"""Calculate path graph kernels up to depth/hight h between graphs.
"""Compute path graph kernels up to depth/hight h between graphs.
Parameters Parameters
---------- ----------
Gn : List of NetworkX graph 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 G1, G2 : NetworkX graphs
Two graphs between which the kernel is calculated.
Two graphs between which the kernel is computed.


node_label : string node_label : string
Node attribute used as label. The default node label is atom. Node attribute used as label. The default node label is atom.
@@ -91,7 +91,7 @@ def untilhpathkernel(*args,
attr_names=['node_labeled', 'node_attr_dim', 'edge_labeled', attr_names=['node_labeled', 'node_attr_dim', 'edge_labeled',
'edge_attr_dim', 'is_directed'], 'edge_attr_dim', 'is_directed'],
node_label=node_label, edge_label=edge_label) node_label=node_label, edge_label=edge_label)
if k_func != None:
if k_func is not None:
if not ds_attrs['node_labeled']: if not ds_attrs['node_labeled']:
for G in Gn: for G in Gn:
nx.set_node_attributes(G, '0', 'atom') nx.set_node_attributes(G, '0', 'atom')
@@ -103,7 +103,7 @@ def untilhpathkernel(*args,


if parallel == 'imap_unordered': if parallel == 'imap_unordered':
# ---- use pool.imap_unordered to parallel and track progress. ---- # ---- use pool.imap_unordered to parallel and track progress. ----
# 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. # but this may cost a lot of memory for large datasets.
pool = Pool(n_jobs) pool = Pool(n_jobs)
itr = zip(Gn, range(0, len(Gn))) itr = zip(Gn, range(0, len(Gn)))
@@ -113,10 +113,10 @@ def untilhpathkernel(*args,
else: else:
chunksize = 100 chunksize = 100
all_paths = [[] for _ in range(len(Gn))] all_paths = [[] for _ in range(len(Gn))]
if compute_method == 'trie' and k_func != None:
if compute_method == 'trie' and k_func is not None:
getps_partial = partial(wrapper_find_all_path_as_trie, depth, getps_partial = partial(wrapper_find_all_path_as_trie, depth,
ds_attrs, node_label, edge_label) ds_attrs, node_label, edge_label)
elif compute_method != 'trie' and k_func != None:
elif compute_method != 'trie' and k_func is not None:
getps_partial = partial(wrapper_find_all_paths_until_length, depth, getps_partial = partial(wrapper_find_all_paths_until_length, depth,
ds_attrs, node_label, edge_label, True) ds_attrs, node_label, edge_label, True)
else: else:
@@ -133,9 +133,9 @@ def untilhpathkernel(*args,
pool.join() pool.join()
# for g in Gn: # for g in Gn:
# if compute_method == 'trie' and k_func != None:
# if compute_method == 'trie' and k_func is not None:
# find_all_path_as_trie(g, depth, ds_attrs, node_label, edge_label) # find_all_path_as_trie(g, depth, ds_attrs, node_label, edge_label)
# elif compute_method != 'trie' and k_func != None:
# elif compute_method != 'trie' and k_func is not None:
# find_all_paths_until_length(g, depth, ds_attrs, node_label, edge_label) # find_all_paths_until_length(g, depth, ds_attrs, node_label, edge_label)
# else: # else:
# find_all_paths_until_length(g, depth, ds_attrs, node_label, edge_label, False) # find_all_paths_until_length(g, depth, ds_attrs, node_label, edge_label, False)
@@ -155,14 +155,14 @@ def untilhpathkernel(*args,
## all_paths[i] = ps ## all_paths[i] = ps
## print(time.time() - ttt) ## print(time.time() - ttt)
if compute_method == 'trie' and k_func != None:
if compute_method == 'trie' and k_func is not None:
def init_worker(trie_toshare): def init_worker(trie_toshare):
global G_trie global G_trie
G_trie = trie_toshare G_trie = trie_toshare
do_partial = partial(wrapper_uhpath_do_trie, k_func) do_partial = partial(wrapper_uhpath_do_trie, k_func)
parallel_gm(do_partial, Kmatrix, Gn, init_worker=init_worker, parallel_gm(do_partial, Kmatrix, Gn, init_worker=init_worker,
glbv=(all_paths,), n_jobs=n_jobs, chunksize=chunksize, verbose=verbose) glbv=(all_paths,), n_jobs=n_jobs, chunksize=chunksize, verbose=verbose)
elif compute_method != 'trie' and k_func != None:
elif compute_method != 'trie' and k_func is not None:
def init_worker(plist_toshare): def init_worker(plist_toshare):
global G_plist global G_plist
G_plist = plist_toshare G_plist = plist_toshare
@@ -177,7 +177,7 @@ def untilhpathkernel(*args,
parallel_gm(do_partial, Kmatrix, Gn, init_worker=init_worker, parallel_gm(do_partial, Kmatrix, Gn, init_worker=init_worker,
glbv=(all_paths,), n_jobs=n_jobs, chunksize=chunksize, verbose=verbose) glbv=(all_paths,), n_jobs=n_jobs, chunksize=chunksize, verbose=verbose)
elif parallel == None:
elif parallel is None:
# from pympler import asizeof # from pympler import asizeof
# ---- direct running, normally use single CPU core. ---- # ---- direct running, normally use single CPU core. ----
# print(asizeof.asized(all_paths, detail=1).format()) # print(asizeof.asized(all_paths, detail=1).format())
@@ -195,7 +195,7 @@ def untilhpathkernel(*args,
# print(sizeof_allpaths) # print(sizeof_allpaths)
pbar = tqdm( pbar = tqdm(
total=((len(Gn) + 1) * len(Gn) / 2), total=((len(Gn) + 1) * len(Gn) / 2),
desc='calculating kernels',
desc='Computing kernels',
file=sys.stdout) file=sys.stdout)
for i in range(0, len(Gn)): for i in range(0, len(Gn)):
for j in range(i, len(Gn)): for j in range(i, len(Gn)):
@@ -217,7 +217,7 @@ def untilhpathkernel(*args,
# print(sizeof_allpaths) # print(sizeof_allpaths)
pbar = tqdm( pbar = tqdm(
total=((len(Gn) + 1) * len(Gn) / 2), total=((len(Gn) + 1) * len(Gn) / 2),
desc='calculating kernels',
desc='Computing kernels',
file=sys.stdout) file=sys.stdout)
for i in range(0, len(Gn)): for i in range(0, len(Gn)):
for j in range(i, len(Gn)): for j in range(i, len(Gn)):
@@ -236,7 +236,7 @@ def untilhpathkernel(*args,




def _untilhpathkernel_do_trie(trie1, trie2, k_func): def _untilhpathkernel_do_trie(trie1, trie2, k_func):
"""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 Parameters
---------- ----------
@@ -351,7 +351,7 @@ def wrapper_uhpath_do_trie(k_func, itr):


def _untilhpathkernel_do_naive(paths1, paths2, k_func): def _untilhpathkernel_do_naive(paths1, paths2, k_func):
"""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 Parameters
---------- ----------
@@ -400,7 +400,7 @@ def wrapper_uhpath_do_naive(k_func, itr):




def _untilhpathkernel_do_kernelless(paths1, paths2, k_func): def _untilhpathkernel_do_kernelless(paths1, paths2, k_func):
"""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 Parameters
---------- ----------


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