Based on the reference provided by Alan Donovan, which says you should use the path matrix (which has a 1 if there is a path from node i to node j) instead of the adjacency matrix (which has a 1 only if there is an edge from node i to node j).
Some sample python code follows below to show the differences between the solutions
def prima(m, title=None):
""" Prints a matrix to the terminal """
if title:
print title
for row in m:
print ', '.join([str(x) for x in row])
print ''
def path(m):
""" Returns a path matrix """
p = [list(row) for row in m]
n = len(p)
for i in xrange(0, n):
for j in xrange(0, n):
if i == j:
continue
if p[j][i]:
for k in xrange(0, n):
if p[j][k] == 0:
p[j][k] = p[i][k]
return p
def hsu(m):
""" Transforms a given directed acyclic graph into its minimal equivalent """
n = len(m)
for j in xrange(n):
for i in xrange(n):
if m[i][j]:
for k in xrange(n):
if m[j][k]:
m[i][k] = 0
m = [ [0, 1, 1, 0, 0],
[0, 0, 0, 0, 0],
[0, 0, 0, 1, 1],
[0, 0, 0, 0, 1],
[0, 1, 0, 0, 0]]
prima(m, 'Original matrix')
hsu(m)
prima(m, 'After Hsu')
p = path(m)
prima(p, 'Path matrix')
hsu(p)
prima(p, 'After Hsu')
Output:
Adjacency matrix
0, 1, 1, 0, 0
0, 0, 0, 0, 0
0, 0, 0, 1, 1
0, 0, 0, 0, 1
0, 1, 0, 0, 0
After Hsu
0, 1, 1, 0, 0
0, 0, 0, 0, 0
0, 0, 0, 1, 0
0, 0, 0, 0, 1
0, 1, 0, 0, 0
Path matrix
0, 1, 1, 1, 1
0, 0, 0, 0, 0
0, 1, 0, 1, 1
0, 1, 0, 0, 1
0, 1, 0, 0, 0
After Hsu
0, 0, 1, 0, 0
0, 0, 0, 0, 0
0, 0, 0, 1, 0
0, 0, 0, 0, 1
0, 1, 0, 0, 0
answered 2013-05-03T11:16:02.203