|
|
@@ -28,16 +28,16 @@ class Treelet(GraphKernel): |
|
|
|
|
|
|
|
def __init__(self, **kwargs): |
|
|
|
GraphKernel.__init__(self) |
|
|
|
self.__node_labels = kwargs.get('node_labels', []) |
|
|
|
self.__edge_labels = kwargs.get('edge_labels', []) |
|
|
|
self.__sub_kernel = kwargs.get('sub_kernel', None) |
|
|
|
self.__ds_infos = kwargs.get('ds_infos', {}) |
|
|
|
if self.__sub_kernel is None: |
|
|
|
self._node_labels = kwargs.get('node_labels', []) |
|
|
|
self._edge_labels = kwargs.get('edge_labels', []) |
|
|
|
self._sub_kernel = kwargs.get('sub_kernel', None) |
|
|
|
self._ds_infos = kwargs.get('ds_infos', {}) |
|
|
|
if self._sub_kernel is None: |
|
|
|
raise Exception('Sub kernel not set.') |
|
|
|
|
|
|
|
|
|
|
|
def _compute_gm_series(self): |
|
|
|
self.__add_dummy_labels(self._graphs) |
|
|
|
self._add_dummy_labels(self._graphs) |
|
|
|
|
|
|
|
# get all canonical keys of all graphs before computing kernels to save |
|
|
|
# time, but this may cost a lot of memory for large dataset. |
|
|
@@ -47,7 +47,7 @@ class Treelet(GraphKernel): |
|
|
|
else: |
|
|
|
iterator = self._graphs |
|
|
|
for g in iterator: |
|
|
|
canonkeys.append(self.__get_canonkeys(g)) |
|
|
|
canonkeys.append(self._get_canonkeys(g)) |
|
|
|
|
|
|
|
# compute Gram matrix. |
|
|
|
gram_matrix = np.zeros((len(self._graphs), len(self._graphs))) |
|
|
@@ -59,7 +59,7 @@ class Treelet(GraphKernel): |
|
|
|
else: |
|
|
|
iterator = itr |
|
|
|
for i, j in iterator: |
|
|
|
kernel = self.__kernel_do(canonkeys[i], canonkeys[j]) |
|
|
|
kernel = self._kernel_do(canonkeys[i], canonkeys[j]) |
|
|
|
gram_matrix[i][j] = kernel |
|
|
|
gram_matrix[j][i] = kernel # @todo: no directed graph considered? |
|
|
|
|
|
|
@@ -67,7 +67,7 @@ class Treelet(GraphKernel): |
|
|
|
|
|
|
|
|
|
|
|
def _compute_gm_imap_unordered(self): |
|
|
|
self.__add_dummy_labels(self._graphs) |
|
|
|
self._add_dummy_labels(self._graphs) |
|
|
|
|
|
|
|
# get all canonical keys of all graphs before computing kernels to save |
|
|
|
# time, but this may cost a lot of memory for large dataset. |
|
|
@@ -103,18 +103,18 @@ class Treelet(GraphKernel): |
|
|
|
|
|
|
|
|
|
|
|
def _compute_kernel_list_series(self, g1, g_list): |
|
|
|
self.__add_dummy_labels(g_list + [g1]) |
|
|
|
self._add_dummy_labels(g_list + [g1]) |
|
|
|
|
|
|
|
# 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_1 = self.__get_canonkeys(g1) |
|
|
|
canonkeys_1 = self._get_canonkeys(g1) |
|
|
|
canonkeys_list = [] |
|
|
|
if self._verbose >= 2: |
|
|
|
iterator = tqdm(g_list, desc='getting canonkeys', file=sys.stdout) |
|
|
|
else: |
|
|
|
iterator = g_list |
|
|
|
for g in iterator: |
|
|
|
canonkeys_list.append(self.__get_canonkeys(g)) |
|
|
|
canonkeys_list.append(self._get_canonkeys(g)) |
|
|
|
|
|
|
|
# compute kernel list. |
|
|
|
kernel_list = [None] * len(g_list) |
|
|
@@ -123,18 +123,18 @@ class Treelet(GraphKernel): |
|
|
|
else: |
|
|
|
iterator = range(len(g_list)) |
|
|
|
for i in iterator: |
|
|
|
kernel = self.__kernel_do(canonkeys_1, canonkeys_list[i]) |
|
|
|
kernel = self._kernel_do(canonkeys_1, canonkeys_list[i]) |
|
|
|
kernel_list[i] = kernel |
|
|
|
|
|
|
|
return kernel_list |
|
|
|
|
|
|
|
|
|
|
|
def _compute_kernel_list_imap_unordered(self, g1, g_list): |
|
|
|
self.__add_dummy_labels(g_list + [g1]) |
|
|
|
self._add_dummy_labels(g_list + [g1]) |
|
|
|
|
|
|
|
# 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_1 = self.__get_canonkeys(g1) |
|
|
|
canonkeys_1 = self._get_canonkeys(g1) |
|
|
|
canonkeys_list = [[] for _ in range(len(g_list))] |
|
|
|
pool = Pool(self._n_jobs) |
|
|
|
itr = zip(g_list, range(0, len(g_list))) |
|
|
@@ -173,18 +173,18 @@ class Treelet(GraphKernel): |
|
|
|
|
|
|
|
|
|
|
|
def _wrapper_kernel_list_do(self, itr): |
|
|
|
return itr, self.__kernel_do(G_ck_1, G_ck_list[itr]) |
|
|
|
return itr, self._kernel_do(G_ck_1, G_ck_list[itr]) |
|
|
|
|
|
|
|
|
|
|
|
def _compute_single_kernel_series(self, g1, g2): |
|
|
|
self.__add_dummy_labels([g1] + [g2]) |
|
|
|
canonkeys_1 = self.__get_canonkeys(g1) |
|
|
|
canonkeys_2 = self.__get_canonkeys(g2) |
|
|
|
kernel = self.__kernel_do(canonkeys_1, canonkeys_2) |
|
|
|
self._add_dummy_labels([g1] + [g2]) |
|
|
|
canonkeys_1 = self._get_canonkeys(g1) |
|
|
|
canonkeys_2 = self._get_canonkeys(g2) |
|
|
|
kernel = self._kernel_do(canonkeys_1, canonkeys_2) |
|
|
|
return kernel |
|
|
|
|
|
|
|
|
|
|
|
def __kernel_do(self, canonkey1, canonkey2): |
|
|
|
def _kernel_do(self, canonkey1, canonkey2): |
|
|
|
"""Compute treelet graph kernel between 2 graphs. |
|
|
|
|
|
|
|
Parameters |
|
|
@@ -200,17 +200,17 @@ class Treelet(GraphKernel): |
|
|
|
keys = set(canonkey1.keys()) & set(canonkey2.keys()) # find same canonical keys in both graphs |
|
|
|
vector1 = np.array([(canonkey1[key] if (key in canonkey1.keys()) else 0) for key in keys]) |
|
|
|
vector2 = np.array([(canonkey2[key] if (key in canonkey2.keys()) else 0) for key in keys]) |
|
|
|
kernel = self.__sub_kernel(vector1, vector2) |
|
|
|
kernel = self._sub_kernel(vector1, vector2) |
|
|
|
return kernel |
|
|
|
|
|
|
|
|
|
|
|
def _wrapper_kernel_do(self, itr): |
|
|
|
i = itr[0] |
|
|
|
j = itr[1] |
|
|
|
return i, j, self.__kernel_do(G_canonkeys[i], G_canonkeys[j]) |
|
|
|
return i, j, self._kernel_do(G_canonkeys[i], G_canonkeys[j]) |
|
|
|
|
|
|
|
|
|
|
|
def __get_canonkeys(self, G): |
|
|
|
def _get_canonkeys(self, G): |
|
|
|
"""Generate canonical keys of all treelets in a graph. |
|
|
|
|
|
|
|
Parameters |
|
|
@@ -236,7 +236,7 @@ class Treelet(GraphKernel): |
|
|
|
patterns['0'] = list(G.nodes()) |
|
|
|
canonkey['0'] = nx.number_of_nodes(G) |
|
|
|
for i in range(1, 6): # for i in range(1, 6): |
|
|
|
patterns[str(i)] = find_all_paths(G, i, self.__ds_infos['directed']) |
|
|
|
patterns[str(i)] = find_all_paths(G, i, self._ds_infos['directed']) |
|
|
|
canonkey[str(i)] = len(patterns[str(i)]) |
|
|
|
|
|
|
|
# n-star patterns |
|
|
@@ -330,11 +330,11 @@ class Treelet(GraphKernel): |
|
|
|
### pattern obtained in the structural analysis section above, which is a |
|
|
|
### string corresponding to a unique treelet. A dictionary is built to keep |
|
|
|
### track of the amount of every treelet. |
|
|
|
if len(self.__node_labels) > 0 or len(self.__edge_labels) > 0: |
|
|
|
if len(self._node_labels) > 0 or len(self._edge_labels) > 0: |
|
|
|
canonkey_l = {} # canonical key, a dictionary which keeps track of amount of every treelet. |
|
|
|
|
|
|
|
# linear patterns |
|
|
|
canonkey_t = Counter(get_mlti_dim_node_attrs(G, self.__node_labels)) |
|
|
|
canonkey_t = Counter(get_mlti_dim_node_attrs(G, self._node_labels)) |
|
|
|
for key in canonkey_t: |
|
|
|
canonkey_l[('0', key)] = canonkey_t[key] |
|
|
|
|
|
|
@@ -343,9 +343,9 @@ class Treelet(GraphKernel): |
|
|
|
for pattern in patterns[str(i)]: |
|
|
|
canonlist = [] |
|
|
|
for idx, node in enumerate(pattern[:-1]): |
|
|
|
canonlist.append(tuple(G.nodes[node][nl] for nl in self.__node_labels)) |
|
|
|
canonlist.append(tuple(G[node][pattern[idx+1]][el] for el in self.__edge_labels)) |
|
|
|
canonlist.append(tuple(G.nodes[pattern[-1]][nl] for nl in self.__node_labels)) |
|
|
|
canonlist.append(tuple(G.nodes[node][nl] for nl in self._node_labels)) |
|
|
|
canonlist.append(tuple(G[node][pattern[idx+1]][el] for el in self._edge_labels)) |
|
|
|
canonlist.append(tuple(G.nodes[pattern[-1]][nl] for nl in self._node_labels)) |
|
|
|
canonkey_t = canonlist if canonlist < canonlist[::-1] else canonlist[::-1] |
|
|
|
treelet.append(tuple([str(i)] + canonkey_t)) |
|
|
|
canonkey_l.update(Counter(treelet)) |
|
|
@@ -356,13 +356,13 @@ class Treelet(GraphKernel): |
|
|
|
for pattern in patterns[str(i) + 'star']: |
|
|
|
canonlist = [] |
|
|
|
for leaf in pattern[1:]: |
|
|
|
nlabels = tuple(G.nodes[leaf][nl] for nl in self.__node_labels) |
|
|
|
elabels = tuple(G[leaf][pattern[0]][el] for el in self.__edge_labels) |
|
|
|
nlabels = tuple(G.nodes[leaf][nl] for nl in self._node_labels) |
|
|
|
elabels = tuple(G[leaf][pattern[0]][el] for el in self._edge_labels) |
|
|
|
canonlist.append(tuple((nlabels, elabels))) |
|
|
|
canonlist.sort() |
|
|
|
canonlist = list(chain.from_iterable(canonlist)) |
|
|
|
canonkey_t = tuple(['d' if i == 5 else str(i * 2)] + |
|
|
|
[tuple(G.nodes[pattern[0]][nl] for nl in self.__node_labels)] |
|
|
|
[tuple(G.nodes[pattern[0]][nl] for nl in self._node_labels)] |
|
|
|
+ canonlist) |
|
|
|
treelet.append(canonkey_t) |
|
|
|
canonkey_l.update(Counter(treelet)) |
|
|
@@ -372,17 +372,17 @@ class Treelet(GraphKernel): |
|
|
|
for pattern in patterns['7']: |
|
|
|
canonlist = [] |
|
|
|
for leaf in pattern[1:3]: |
|
|
|
nlabels = tuple(G.nodes[leaf][nl] for nl in self.__node_labels) |
|
|
|
elabels = tuple(G[leaf][pattern[0]][el] for el in self.__edge_labels) |
|
|
|
nlabels = tuple(G.nodes[leaf][nl] for nl in self._node_labels) |
|
|
|
elabels = tuple(G[leaf][pattern[0]][el] for el in self._edge_labels) |
|
|
|
canonlist.append(tuple((nlabels, elabels))) |
|
|
|
canonlist.sort() |
|
|
|
canonlist = list(chain.from_iterable(canonlist)) |
|
|
|
canonkey_t = tuple(['7'] |
|
|
|
+ [tuple(G.nodes[pattern[0]][nl] for nl in self.__node_labels)] + canonlist |
|
|
|
+ [tuple(G.nodes[pattern[3]][nl] for nl in self.__node_labels)] |
|
|
|
+ [tuple(G[pattern[3]][pattern[0]][el] for el in self.__edge_labels)] |
|
|
|
+ [tuple(G.nodes[pattern[4]][nl] for nl in self.__node_labels)] |
|
|
|
+ [tuple(G[pattern[4]][pattern[3]][el] for el in self.__edge_labels)]) |
|
|
|
+ [tuple(G.nodes[pattern[0]][nl] for nl in self._node_labels)] + canonlist |
|
|
|
+ [tuple(G.nodes[pattern[3]][nl] for nl in self._node_labels)] |
|
|
|
+ [tuple(G[pattern[3]][pattern[0]][el] for el in self._edge_labels)] |
|
|
|
+ [tuple(G.nodes[pattern[4]][nl] for nl in self._node_labels)] |
|
|
|
+ [tuple(G[pattern[4]][pattern[3]][el] for el in self._edge_labels)]) |
|
|
|
treelet.append(canonkey_t) |
|
|
|
canonkey_l.update(Counter(treelet)) |
|
|
|
|
|
|
@@ -391,38 +391,38 @@ class Treelet(GraphKernel): |
|
|
|
for pattern in patterns['11']: |
|
|
|
canonlist = [] |
|
|
|
for leaf in pattern[1:4]: |
|
|
|
nlabels = tuple(G.nodes[leaf][nl] for nl in self.__node_labels) |
|
|
|
elabels = tuple(G[leaf][pattern[0]][el] for el in self.__edge_labels) |
|
|
|
nlabels = tuple(G.nodes[leaf][nl] for nl in self._node_labels) |
|
|
|
elabels = tuple(G[leaf][pattern[0]][el] for el in self._edge_labels) |
|
|
|
canonlist.append(tuple((nlabels, elabels))) |
|
|
|
canonlist.sort() |
|
|
|
canonlist = list(chain.from_iterable(canonlist)) |
|
|
|
canonkey_t = tuple(['b'] |
|
|
|
+ [tuple(G.nodes[pattern[0]][nl] for nl in self.__node_labels)] + canonlist |
|
|
|
+ [tuple(G.nodes[pattern[4]][nl] for nl in self.__node_labels)] |
|
|
|
+ [tuple(G[pattern[4]][pattern[0]][el] for el in self.__edge_labels)] |
|
|
|
+ [tuple(G.nodes[pattern[5]][nl] for nl in self.__node_labels)] |
|
|
|
+ [tuple(G[pattern[5]][pattern[4]][el] for el in self.__edge_labels)]) |
|
|
|
+ [tuple(G.nodes[pattern[0]][nl] for nl in self._node_labels)] + canonlist |
|
|
|
+ [tuple(G.nodes[pattern[4]][nl] for nl in self._node_labels)] |
|
|
|
+ [tuple(G[pattern[4]][pattern[0]][el] for el in self._edge_labels)] |
|
|
|
+ [tuple(G.nodes[pattern[5]][nl] for nl in self._node_labels)] |
|
|
|
+ [tuple(G[pattern[5]][pattern[4]][el] for el in self._edge_labels)]) |
|
|
|
treelet.append(canonkey_t) |
|
|
|
canonkey_l.update(Counter(treelet)) |
|
|
|
|
|
|
|
# pattern 10 |
|
|
|
treelet = [] |
|
|
|
for pattern in patterns['10']: |
|
|
|
canonkey4 = [tuple(G.nodes[pattern[5]][nl] for nl in self.__node_labels), |
|
|
|
tuple(G[pattern[5]][pattern[4]][el] for el in self.__edge_labels)] |
|
|
|
canonkey4 = [tuple(G.nodes[pattern[5]][nl] for nl in self._node_labels), |
|
|
|
tuple(G[pattern[5]][pattern[4]][el] for el in self._edge_labels)] |
|
|
|
canonlist = [] |
|
|
|
for leaf in pattern[1:3]: |
|
|
|
nlabels = tuple(G.nodes[leaf][nl] for nl in self.__node_labels) |
|
|
|
elabels = tuple(G[leaf][pattern[0]][el] for el in self.__edge_labels) |
|
|
|
nlabels = tuple(G.nodes[leaf][nl] for nl in self._node_labels) |
|
|
|
elabels = tuple(G[leaf][pattern[0]][el] for el in self._edge_labels) |
|
|
|
canonlist.append(tuple((nlabels, elabels))) |
|
|
|
canonlist.sort() |
|
|
|
canonkey0 = list(chain.from_iterable(canonlist)) |
|
|
|
canonkey_t = tuple(['a'] |
|
|
|
+ [tuple(G.nodes[pattern[3]][nl] for nl in self.__node_labels)] |
|
|
|
+ [tuple(G.nodes[pattern[4]][nl] for nl in self.__node_labels)] |
|
|
|
+ [tuple(G[pattern[4]][pattern[3]][el] for el in self.__edge_labels)] |
|
|
|
+ [tuple(G.nodes[pattern[0]][nl] for nl in self.__node_labels)] |
|
|
|
+ [tuple(G[pattern[0]][pattern[3]][el] for el in self.__edge_labels)] |
|
|
|
+ [tuple(G.nodes[pattern[3]][nl] for nl in self._node_labels)] |
|
|
|
+ [tuple(G.nodes[pattern[4]][nl] for nl in self._node_labels)] |
|
|
|
+ [tuple(G[pattern[4]][pattern[3]][el] for el in self._edge_labels)] |
|
|
|
+ [tuple(G.nodes[pattern[0]][nl] for nl in self._node_labels)] |
|
|
|
+ [tuple(G[pattern[0]][pattern[3]][el] for el in self._edge_labels)] |
|
|
|
+ canonkey4 + canonkey0) |
|
|
|
treelet.append(canonkey_t) |
|
|
|
canonkey_l.update(Counter(treelet)) |
|
|
@@ -432,15 +432,15 @@ class Treelet(GraphKernel): |
|
|
|
for pattern in patterns['12']: |
|
|
|
canonlist0 = [] |
|
|
|
for leaf in pattern[1:3]: |
|
|
|
nlabels = tuple(G.nodes[leaf][nl] for nl in self.__node_labels) |
|
|
|
elabels = tuple(G[leaf][pattern[0]][el] for el in self.__edge_labels) |
|
|
|
nlabels = tuple(G.nodes[leaf][nl] for nl in self._node_labels) |
|
|
|
elabels = tuple(G[leaf][pattern[0]][el] for el in self._edge_labels) |
|
|
|
canonlist0.append(tuple((nlabels, elabels))) |
|
|
|
canonlist0.sort() |
|
|
|
canonlist0 = list(chain.from_iterable(canonlist0)) |
|
|
|
canonlist3 = [] |
|
|
|
for leaf in pattern[4:6]: |
|
|
|
nlabels = tuple(G.nodes[leaf][nl] for nl in self.__node_labels) |
|
|
|
elabels = tuple(G[leaf][pattern[3]][el] for el in self.__edge_labels) |
|
|
|
nlabels = tuple(G.nodes[leaf][nl] for nl in self._node_labels) |
|
|
|
elabels = tuple(G[leaf][pattern[3]][el] for el in self._edge_labels) |
|
|
|
canonlist3.append(tuple((nlabels, elabels))) |
|
|
|
canonlist3.sort() |
|
|
|
canonlist3 = list(chain.from_iterable(canonlist3)) |
|
|
@@ -448,14 +448,14 @@ class Treelet(GraphKernel): |
|
|
|
# 2 possible key can be generated from 2 nodes with extended label 3, |
|
|
|
# select the one with lower lexicographic order. |
|
|
|
canonkey_t1 = tuple(['c'] |
|
|
|
+ [tuple(G.nodes[pattern[0]][nl] for nl in self.__node_labels)] + canonlist0 |
|
|
|
+ [tuple(G.nodes[pattern[3]][nl] for nl in self.__node_labels)] |
|
|
|
+ [tuple(G[pattern[3]][pattern[0]][el] for el in self.__edge_labels)] |
|
|
|
+ [tuple(G.nodes[pattern[0]][nl] for nl in self._node_labels)] + canonlist0 |
|
|
|
+ [tuple(G.nodes[pattern[3]][nl] for nl in self._node_labels)] |
|
|
|
+ [tuple(G[pattern[3]][pattern[0]][el] for el in self._edge_labels)] |
|
|
|
+ canonlist3) |
|
|
|
canonkey_t2 = tuple(['c'] |
|
|
|
+ [tuple(G.nodes[pattern[3]][nl] for nl in self.__node_labels)] + canonlist3 |
|
|
|
+ [tuple(G.nodes[pattern[0]][nl] for nl in self.__node_labels)] |
|
|
|
+ [tuple(G[pattern[0]][pattern[3]][el] for el in self.__edge_labels)] |
|
|
|
+ [tuple(G.nodes[pattern[3]][nl] for nl in self._node_labels)] + canonlist3 |
|
|
|
+ [tuple(G.nodes[pattern[0]][nl] for nl in self._node_labels)] |
|
|
|
+ [tuple(G[pattern[0]][pattern[3]][el] for el in self._edge_labels)] |
|
|
|
+ canonlist0) |
|
|
|
treelet.append(canonkey_t1 if canonkey_t1 < canonkey_t2 else canonkey_t2) |
|
|
|
canonkey_l.update(Counter(treelet)) |
|
|
@@ -463,24 +463,24 @@ class Treelet(GraphKernel): |
|
|
|
# pattern 9 |
|
|
|
treelet = [] |
|
|
|
for pattern in patterns['9']: |
|
|
|
canonkey2 = [tuple(G.nodes[pattern[4]][nl] for nl in self.__node_labels), |
|
|
|
tuple(G[pattern[4]][pattern[2]][el] for el in self.__edge_labels)] |
|
|
|
canonkey3 = [tuple(G.nodes[pattern[5]][nl] for nl in self.__node_labels), |
|
|
|
tuple(G[pattern[5]][pattern[3]][el] for el in self.__edge_labels)] |
|
|
|
prekey2 = [tuple(G.nodes[pattern[2]][nl] for nl in self.__node_labels), |
|
|
|
tuple(G[pattern[2]][pattern[0]][el] for el in self.__edge_labels)] |
|
|
|
prekey3 = [tuple(G.nodes[pattern[3]][nl] for nl in self.__node_labels), |
|
|
|
tuple(G[pattern[3]][pattern[0]][el] for el in self.__edge_labels)] |
|
|
|
canonkey2 = [tuple(G.nodes[pattern[4]][nl] for nl in self._node_labels), |
|
|
|
tuple(G[pattern[4]][pattern[2]][el] for el in self._edge_labels)] |
|
|
|
canonkey3 = [tuple(G.nodes[pattern[5]][nl] for nl in self._node_labels), |
|
|
|
tuple(G[pattern[5]][pattern[3]][el] for el in self._edge_labels)] |
|
|
|
prekey2 = [tuple(G.nodes[pattern[2]][nl] for nl in self._node_labels), |
|
|
|
tuple(G[pattern[2]][pattern[0]][el] for el in self._edge_labels)] |
|
|
|
prekey3 = [tuple(G.nodes[pattern[3]][nl] for nl in self._node_labels), |
|
|
|
tuple(G[pattern[3]][pattern[0]][el] for el in self._edge_labels)] |
|
|
|
if prekey2 + canonkey2 < prekey3 + canonkey3: |
|
|
|
canonkey_t = [tuple(G.nodes[pattern[1]][nl] for nl in self.__node_labels)] \ |
|
|
|
+ [tuple(G[pattern[1]][pattern[0]][el] for el in self.__edge_labels)] \ |
|
|
|
canonkey_t = [tuple(G.nodes[pattern[1]][nl] for nl in self._node_labels)] \ |
|
|
|
+ [tuple(G[pattern[1]][pattern[0]][el] for el in self._edge_labels)] \ |
|
|
|
+ prekey2 + prekey3 + canonkey2 + canonkey3 |
|
|
|
else: |
|
|
|
canonkey_t = [tuple(G.nodes[pattern[1]][nl] for nl in self.__node_labels)] \ |
|
|
|
+ [tuple(G[pattern[1]][pattern[0]][el] for el in self.__edge_labels)] \ |
|
|
|
canonkey_t = [tuple(G.nodes[pattern[1]][nl] for nl in self._node_labels)] \ |
|
|
|
+ [tuple(G[pattern[1]][pattern[0]][el] for el in self._edge_labels)] \ |
|
|
|
+ prekey3 + prekey2 + canonkey3 + canonkey2 |
|
|
|
treelet.append(tuple(['9'] |
|
|
|
+ [tuple(G.nodes[pattern[0]][nl] for nl in self.__node_labels)] |
|
|
|
+ [tuple(G.nodes[pattern[0]][nl] for nl in self._node_labels)] |
|
|
|
+ canonkey_t)) |
|
|
|
canonkey_l.update(Counter(treelet)) |
|
|
|
|
|
|
@@ -492,15 +492,15 @@ class Treelet(GraphKernel): |
|
|
|
def _wrapper_get_canonkeys(self, itr_item): |
|
|
|
g = itr_item[0] |
|
|
|
i = itr_item[1] |
|
|
|
return i, self.__get_canonkeys(g) |
|
|
|
return i, self._get_canonkeys(g) |
|
|
|
|
|
|
|
|
|
|
|
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): |
|
|
|
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): |
|
|
|
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] |
|
|
|
self._edge_labels = [SpecialLabel.DUMMY] |