diff --git a/gmatch4py/base.pxd b/gmatch4py/base.pxd
index e3dd39ec7a44d163ec0761eb9f99fb2850fa8141..930e12ad66a591460bd8fc38c682ae3a63a67127 100644
--- a/gmatch4py/base.pxd
+++ b/gmatch4py/base.pxd
@@ -4,14 +4,15 @@ cdef class Base:
## Attribute(s)
cdef int type_alg
cdef bint normalized
-
+ cdef int cpu_count
## Methods
cpdef np.ndarray compare(self,list graph_list, list selected)
cpdef np.ndarray compare_old(self,list listgs, list selected)
cpdef np.ndarray distance(self, np.ndarray matrix)
cpdef np.ndarray similarity(self, np.ndarray matrix)
cpdef bint isAccepted(self,G,index,selected)
- cpdef list get_selected_array(self,selected,size_corpus)
+ cpdef np.ndarray get_selected_array(self,selected,size_corpus)
+
cpdef intersection(G,H)
cpdef union_(G,H)
diff --git a/gmatch4py/base.pyx b/gmatch4py/base.pyx
index ac993092459d1027e90a17e8e3106a41a5a30962..e9d9b0d915c48a828ce18896a39f6c54a3c88151 100644
--- a/gmatch4py/base.pyx
+++ b/gmatch4py/base.pyx
@@ -3,6 +3,10 @@
import numpy as np
cimport numpy as np
import networkx as nx
+cimport cython
+import multiprocessing
+
+
cpdef np.ndarray minmax_scale(np.ndarray matrix):
"""
@@ -136,17 +140,22 @@ cdef class Base:
else:
self.type_alg=type_alg
self.normalized=normalized
+ self.cpu_count=multiprocessing.cpu_count()
- cpdef list get_selected_array(self,selected,size_corpus):
- cdef list selected_test = [True]*size_corpus
- if selected:
- selected_test = [False]*size_corpus
+ cpdef np.ndarray get_selected_array(self,selected,size_corpus):
+ cdef double[:] selected_test = np.zeros(size_corpus)
+ if not selected == None:
for ix in range(len(selected)):
- selected_test[ix]=True
- return selected
+ selected_test[selected[ix]]=1
+ return np.array(selected_test)
+ else:
+ return np.array(selected_test)+1
+
cpdef np.ndarray compare_old(self,list listgs, list selected):
pass
+
+ @cython.boundscheck(False)
cpdef np.ndarray compare(self,list graph_list, list selected):
"""
Return the similarity/distance matrix using the current algorithm.
diff --git a/gmatch4py/ged/abstract_graph_edit_dist.pyx b/gmatch4py/ged/abstract_graph_edit_dist.pyx
index f4b25fde928a0b0c497be35ba9df2bd7a033fbdf..683da17616a7ffa8bcb0c16cc91e32dc207f6186 100644
--- a/gmatch4py/ged/abstract_graph_edit_dist.pyx
+++ b/gmatch4py/ged/abstract_graph_edit_dist.pyx
@@ -115,17 +115,17 @@ cdef class AbstractGraphEditDistance(Base):
cdef double[:,:] comparison_matrix = np.zeros((n, n))
listgs=parsenx2graph(listgs)
cdef long[:] n_nodes = np.array([g.size() for g in listgs])
-
- cdef bint[:] selected_test = self.get_selected_array(selected,n)
+ cdef double[:] selected_test = np.array(self.get_selected_array(selected,n))
cdef int i,j
val=np.inf
- with nogil, parallel(num_threads=8):
+
+ with nogil, parallel(num_threads=self.cpu_count):
for i in prange(n,schedule='static'):
for j in range(n):
- if n_nodes[i]>0 and n_nodes[j]>0 and selected_test[i] :
- with gil:
- comparison_matrix[i][j] = self.distance_ged(listgs[i],listgs[j])
- else:
- comparison_matrix[i][j] = 0
- #comparison_matrix[j, i] = comparison_matrix[i, j]
+ if n_nodes[i]>0 and n_nodes[j]>0 and selected_test[i] == 1 :
+ with gil:
+ comparison_matrix[i][j] = self.distance_ged(listgs[i],listgs[j])
+ else:
+ comparison_matrix[i][j] = 0
+ #comparison_matrix[j, i] = comparison_matrix[i, j]
return np.array(comparison_matrix)
diff --git a/gmatch4py/ged/bipartite_graph_matching_2.pyx b/gmatch4py/ged/bipartite_graph_matching_2.pyx
index 45fd67f625450c68d0579634de6d652430cfdd14..faef03ab776f3b4f122cd147647dc3b976e056f7 100644
--- a/gmatch4py/ged/bipartite_graph_matching_2.pyx
+++ b/gmatch4py/ged/bipartite_graph_matching_2.pyx
@@ -53,22 +53,22 @@ cdef class BP_2(Base):
cdef int n = len(listgs)
cdef list new_gs=parsenx2graph(listgs)
cdef double[:,:] comparison_matrix = np.zeros((n, n))
- cdef bint[:] selected_test = self.get_selected_array(selected,n)
+ cdef double[:] selected_test = self.get_selected_array(selected,n)
cdef int i,j
cdef long[:] n_nodes = np.array([g.size() for g in new_gs])
cdef long[:] n_edges = np.array([g.density() for g in new_gs])
- with nogil, parallel(num_threads=4):
+ with nogil, parallel(num_threads=self.cpu_count):
for i in prange(n,schedule='static'):
for j in range(i,n):
- if n_nodes[i] > 0 and n_nodes[j] > 0 and selected_test[i] == True:
+ if n_nodes[i] > 0 and n_nodes[j] > 0 and selected_test[i] == 1:
with gil:
comparison_matrix[i, j] = self.bp2(new_gs[i], new_gs[j])
else:
comparison_matrix[i, j] = 0
comparison_matrix[j, i] = comparison_matrix[i, j]
- return comparison_matrix
+ return np.array(comparison_matrix)
cdef double bp2(self, g1, g2):
@@ -148,18 +148,18 @@ cdef class BP_2(Base):
:return:
"""
cdef np.ndarray min_sum = np.zeros(g1.size())
- nodes1 = list(g1.nodes())
- nodes2 = list(g2.nodes())
+ cdef list nodes1 = list(g1.nodes())
+ cdef list nodes2 = list(g2.nodes())
nodes2.extend([None])
cdef np.ndarray min_i
- for i in range(len(nodes1)):
- min_i = np.zeros(len(nodes2))
- for j in range(len(nodes2)):
+ for i in range(g1.size()):
+ min_i = np.zeros(g2.size())
+ for j in range(g2.size()):
min_i[j] = self.fuv(g1, g2, nodes1[i], nodes2[j])
min_sum[i] = np.min(min_i)
return np.sum(min_sum)
- cdef float fuv(self, g1, g2, n1, n2):
+ cdef float fuv(self, g1, g2, str n1, str n2):
"""
Compute the Node Distance function
:param g1: first graph
@@ -177,7 +177,7 @@ cdef class BP_2(Base):
return 0
return (self.node_del + self.node_ins + self.hed_edge(g1, g2, n1, n2)) / 2
- cdef float hed_edge(self, g1, g2, n1, n2):
+ cdef float hed_edge(self, g1, g2, str n1, str n2):
"""
Compute HEDistance between edges of n1 and n2, respectively in g1 and g2
:param g1: first graph
@@ -189,7 +189,7 @@ cdef class BP_2(Base):
return self.sum_gpq(g1, n1, g2, n2) + self.sum_gpq(g1, n1, g2, n2)
- cdef float sum_gpq(self, g1, n1, g2, n2):
+ cdef float sum_gpq(self, g1, str n1, g2, str n2):
"""
Compute Nearest Neighbour Distance between edges around n1 in G1 and edges around n2 in G2
:param g1: first graph
@@ -213,7 +213,7 @@ cdef class BP_2(Base):
min_sum[i] = np.min(min_i)
return np.sum(min_sum)
- cdef float gpq(self, tuple e1, tuple e2):
+ cdef float gpq(self, str e1, str e2):
"""
Compute the edge distance function
:param e1: edge1
diff --git a/gmatch4py/ged/graph_edit_dist.pyx b/gmatch4py/ged/graph_edit_dist.pyx
index 3706c283884e6f488124812a0627b8fb5316c16c..b1f9346cf79e3bcf96dad6d7231533a47f8fcb9f 100644
--- a/gmatch4py/ged/graph_edit_dist.pyx
+++ b/gmatch4py/ged/graph_edit_dist.pyx
@@ -7,7 +7,6 @@ import numpy as np
cimport numpy as np
from .abstract_graph_edit_dist cimport AbstractGraphEditDistance
from ..base cimport intersection,union_
-from ..graph cimport Graph
cdef class GraphEditDistance(AbstractGraphEditDistance):
diff --git a/gmatch4py/ged/hausdorff_edit_distance.pyx b/gmatch4py/ged/hausdorff_edit_distance.pyx
index a83e2a1897bfd9330d2dd9e8beb30d3abd146fa2..bf6b8fbdfbb93c3275e21fec62dc91d7d1d5232d 100644
--- a/gmatch4py/ged/hausdorff_edit_distance.pyx
+++ b/gmatch4py/ged/hausdorff_edit_distance.pyx
@@ -49,12 +49,12 @@ cdef class HED(Base):
cdef int n = len(listgs)
cdef list new_gs=parsenx2graph(listgs)
cdef double[:,:] comparison_matrix = np.zeros((n, n))
- cdef bint[:] selected_test = self.get_selected_array(selected,n)
+ cdef double[:] selected_test = np.array(self.get_selected_array(selected,n))
cdef int i,j
cdef long[:] n_nodes = np.array([g.size() for g in new_gs])
cdef long[:] n_edges = np.array([g.density() for g in new_gs])
- with nogil, parallel(num_threads=4):
+ with nogil, parallel(num_threads=self.cpu_count):
for i in prange(n,schedule='static'):
for j in range(i,n):
if n_nodes[i] > 0 and n_nodes[j] > 0 and selected_test[i] == True:
@@ -64,7 +64,7 @@ cdef class HED(Base):
comparison_matrix[i, j] = 0
comparison_matrix[j, i] = comparison_matrix[i, j]
- return comparison_matrix
+ return np.array(comparison_matrix)
cdef float hed(self, g1, g2):
@@ -83,19 +83,19 @@ cdef class HED(Base):
:param g2: Second Graph
:return:
"""
- cdef np.ndarray min_sum = np.zeros(len(g1))
- nodes1 = list(g1.nodes())
- nodes2 = list(g2.nodes())
+ cdef np.ndarray min_sum = np.zeros(g1.size())
+ cdef list nodes1 = list(g1.nodes())
+ cdef list nodes2 = list(g2.nodes())
nodes2.extend([None])
cdef np.ndarray min_i
- for i in range(len(nodes1)):
- min_i = np.zeros(len(nodes2))
- for j in range(len(nodes2)):
+ for i in range(g1.size()):
+ min_i = np.zeros(g2.size())
+ for j in range(g2.size()):
min_i[j] = self.fuv(g1, g2, nodes1[i], nodes2[j])
min_sum[i] = np.min(min_i)
return np.sum(min_sum)
- cdef float fuv(self, g1, g2, n1, n2):
+ cdef float fuv(self, g1, g2, str n1, str n2):
"""
Compute the Node Distance function
:param g1: first graph
@@ -113,7 +113,7 @@ cdef class HED(Base):
return 0
return (self.node_del + self.node_ins + self.hed_edge(g1, g2, n1, n2)) / 2
- cdef float hed_edge(self, g1, g2, n1, n2):
+ cdef float hed_edge(self, g1, g2, str n1, str n2):
"""
Compute HEDistance between edges of n1 and n2, respectively in g1 and g2
:param g1: first graph
@@ -125,7 +125,7 @@ cdef class HED(Base):
return self.sum_gpq(g1, n1, g2, n2) + self.sum_gpq(g1, n1, g2, n2)
- cdef float sum_gpq(self, g1, n1, g2, n2):
+ cdef float sum_gpq(self, g1, str n1, g2, str n2):
"""
Compute Nearest Neighbour Distance between edges around n1 in G1 and edges around n2 in G2
:param g1: first graph
@@ -149,7 +149,7 @@ cdef class HED(Base):
min_sum[i] = np.min(min_i)
return np.sum(min_sum)
- cdef float gpq(self, tuple e1, tuple e2):
+ cdef float gpq(self, str e1, str e2):
"""
Compute the edge distance function
:param e1: edge1
diff --git a/gmatch4py/graph.pyx b/gmatch4py/graph.pyx
index 4d3b770b1babedcbab3a77c55711ebcff2c20d23..ac03d698de659cf201a0b428d3d11920ca01e32a 100644
--- a/gmatch4py/graph.pyx
+++ b/gmatch4py/graph.pyx
@@ -207,6 +207,7 @@ cdef class Graph:
return [(e1,e2,self.edges_attr_list[self.edges_hash_idx[hash_]])for hash_ in hashes]
else:
return [(e1,e2,None)]
+
cpdef list get_edges_no(self,str n):
return self.edges_of_nodes[n]
diff --git a/gmatch4py/jaccard.pyx b/gmatch4py/jaccard.pyx
index 99d8b5d03c7fed243a35fd6d56c29e1a80b35710..d69c0ca7123a1992334592f52f57b89f5b8fa342 100644
--- a/gmatch4py/jaccard.pyx
+++ b/gmatch4py/jaccard.pyx
@@ -5,7 +5,7 @@ cimport numpy as np
from .base cimport Base
from .base cimport intersection,union_
-from ..helpers.general import parsenx2graph
+from .helpers.general import parsenx2graph
from cython.parallel cimport prange,parallel
cdef class Jaccard(Base):
@@ -47,7 +47,7 @@ cdef class Jaccard(Base):
cdef long[:] n_edges = np.array([g.density() for g in new_gs])
cdef int i,j
- cdef bint[:] selected_test = self.get_selected_array(selected,n)
+ cdef double[:] selected_test = np.array(self.get_selected_array(selected,n))
cdef double[:,:] intersect_len_nodes = np.zeros((n, n))
cdef double[:,:] intersect_len_edges = np.zeros((n, n))
@@ -59,10 +59,10 @@ cdef class Jaccard(Base):
intersect_len_edges[i][j]=new_gs[i].size_edge_intersect(new_gs[j])#len(set(hash_edges[i]).intersection(hash_edges[j]))
union_len_nodes[i][j]=new_gs[i].size_node_union(new_gs[j])
union_len_edges[i][j]=new_gs[i].size_node_union(new_gs[j])
- with nogil, parallel(num_threads=4):
+ with nogil, parallel(num_threads=self.cpu_count):
for i in prange(n,schedule='static'):
for j in range(i,n):
- if n_nodes[i] > 0 and n_nodes[j] > 0 and selected_test[i]:
+ if n_nodes[i] > 0 and n_nodes[j] > 0 and selected_test[i] == 1:
if union_len_edges[i][j] >0 and union_len_nodes[i][j] >0:
comparison_matrix[i][j]= \
(intersect_len_edges[i][j]/union_len_edges[i][j])*\
diff --git a/gmatch4py/kernels/weisfeiler_lehman.pyx b/gmatch4py/kernels/weisfeiler_lehman.pyx
index 93a78cbbc36b49d0f328198fa7f38a59ea1fa22a..e0e4c0edf80b6012f95784bb178620100a2f64c9 100644
--- a/gmatch4py/kernels/weisfeiler_lehman.pyx
+++ b/gmatch4py/kernels/weisfeiler_lehman.pyx
@@ -105,7 +105,6 @@ cdef class WeisfeleirLehmanKernel(Base):
# cdef np.ndarray[np.float64_t] k
k = np.dot(phi.transpose(), phi)
- print(1)
# MAIN LOOP
cdef int it = 0
diff --git a/gmatch4py/mcs.pyx b/gmatch4py/mcs.pyx
index 9ad07f06926f3568d3a0afb7bbe290ed70581d00..50e09fbba6db257ab1a34350cf7d06f07dbc2f15 100644
--- a/gmatch4py/mcs.pyx
+++ b/gmatch4py/mcs.pyx
@@ -4,7 +4,7 @@ cimport numpy as np
from .graph cimport Graph
from .base cimport Base
from cython.parallel cimport prange,parallel
-from ..helpers.general import parsenx2graph
+from .helpers.general import parsenx2graph
cdef class MCS(Base):
"""
@@ -31,7 +31,7 @@ cdef class MCS(Base):
cpdef np.ndarray compare(self,list listgs, list selected):
cdef int n = len(listgs)
cdef double [:,:] comparison_matrix = np.zeros((n, n))
- cdef bint[:] selected_test = self.get_selected_array(selected,n)
+ cdef double[:] selected_test = np.array(self.get_selected_array(selected,n))
cdef list new_gs=parsenx2graph(listgs)
cdef long[:] n_nodes = np.array([g.size() for g in new_gs])
cdef double [:,:] intersect_len_nodes = np.zeros((n, n))
@@ -40,10 +40,10 @@ cdef class MCS(Base):
for j in range(i,n):
intersect_len_nodes[i][j]=new_gs[i].size_node_intersect(new_gs[j])
- with nogil, parallel(num_threads=4):
+ with nogil, parallel(num_threads=self.cpu_count):
for i in prange(n,schedule='static'):
for j in range(i, n):
- if n_nodes[i] > 0 and n_nodes[j] > 0 and selected_test[i]:
+ if n_nodes[i] > 0 and n_nodes[j] > 0 and selected_test[i] == 1:
comparison_matrix[i][j] = intersect_len_nodes[i][j]/max(n_nodes[i],n_nodes[j])
else:
comparison_matrix[i][j] = 0.
diff --git a/gmatch4py/vertex_edge_overlap.pyx b/gmatch4py/vertex_edge_overlap.pyx
index 3bbe9c7ee496eb91bb200c046fdc53ec23770664..b883c9aeac3fb4a20ba48d3ebf0cf55ce1cf596b 100644
--- a/gmatch4py/vertex_edge_overlap.pyx
+++ b/gmatch4py/vertex_edge_overlap.pyx
@@ -5,7 +5,7 @@ cimport numpy as np
from .base cimport Base,intersection
from .graph cimport Graph
from cython.parallel cimport prange,parallel
-from ..helpers.general import parsenx2graph
+from .helpers.general import parsenx2graph
cdef class VertexEdgeOverlap(Base):
@@ -47,7 +47,7 @@ cdef class VertexEdgeOverlap(Base):
cdef long[:] n_nodes = np.array([g.size() for g in new_gs])
cdef long[:] n_edges = np.array([g.density() for g in new_gs])
- cdef bint[:] selected_test = self.get_selected_array(selected,n)
+ cdef double[:] selected_test = np.array(self.get_selected_array(selected,n))
cdef double[:,:] intersect_len_nodes = np.zeros((n, n))
cdef double[:,:] intersect_len_edges = np.zeros((n, n))
@@ -56,10 +56,10 @@ cdef class VertexEdgeOverlap(Base):
intersect_len_nodes[i][j]=new_gs[i].size_node_intersect(new_gs[j])
intersect_len_edges[i][j]=new_gs[i].size_edge_intersect(new_gs[j])#len(set(hash_edges[i]).intersection(hash_edges[j]))
- with nogil, parallel(num_threads=4):
+ with nogil, parallel(num_threads=self.cpu_count):
for i in prange(n,schedule='static'):
for j in range(i,n):
- if n_nodes[i] > 0 and n_nodes[j] > 0 and selected_test[i] == True:
+ if n_nodes[i] > 0 and n_nodes[j] > 0 and selected_test[i] == 1:
denom=n_nodes[i]+n_nodes[j]+\
n_edges[i]+n_edges[j]
if denom == 0:
diff --git a/setup.py b/setup.py
index 16b9d05a5c4ecb984e4145537bda928a19b553ac..71fcff81e83aed1c91979a981033d1f9c8ddcaef 100644
--- a/setup.py
+++ b/setup.py
@@ -70,7 +70,7 @@ setup(
cmdclass={'build_ext': build_ext},
setup_requires=["numpy","networkx","scipy",'scikit-learn'],
install_requires=["numpy","networkx","scipy",'scikit-learn'],
- version="0.2.2alpha",
+ version="0.2.4alpha",
classifiers=[
"Programming Language :: Python :: 3",
"License :: OSI Approved :: MIT License",
diff --git a/test/real_test.py b/test/real_test.py
index d2753d87a7e48615b9da219afddfc91fd263a6ad..f0fb835c52c5b98928f2211d4dd32e3397320214 100644
--- a/test/real_test.py
+++ b/test/real_test.py
@@ -1 +1,14 @@
from gmatch4py import *
+import networkx as nx
+
+graphs=[nx.random_tree(10) for i in range(10)]
+comparator=None
+for class_ in [BagOfNodes,WeisfeleirLehmanKernel,GraphEditDistance, BP_2, GreedyEditDistance, HED, Jaccard, MCS, VertexEdgeOverlap]:
+ print(class_)
+ if class_ in (GraphEditDistance, BP_2, GreedyEditDistance, HED):
+ comparator = class_(1, 1, 1, 1)
+ elif class_ == WeisfeleirLehmanKernel:
+ comparator = class_(h=2)
+ else:
+ comparator=class_()
+ matrix = comparator.compare(graphs, [])