Example #1
0
    def test_eigenvectors(self):
        try:
            import numpy as N
            eigenval=N.linalg.eigvals
        except ImportError:
            raise SkipTest('NumPy not available.')

        cs='ddiiddid'
        G=nxt.threshold_graph(cs)
        (tgeval,tgevec)=nxt.eigenvectors(cs)
        dot=N.dot
        assert_equal([ abs(dot(lv,lv)-1.0)<1e-9 for lv in tgevec ], [True]*8)
        lapl=nx.laplacian_matrix(G)
Example #2
0
    def test_eigenvectors(self):
        try:
            import numpy as N
            eigenval=N.linalg.eigvals
        except ImportError:
            raise SkipTest('NumPy not available.')

        cs='ddiiddid'
        G=nxt.threshold_graph(cs)
        (tgeval,tgevec)=nxt.eigenvectors(cs)
        dot=N.dot
        assert_equal([ abs(dot(lv,lv)-1.0)<1e-9 for lv in tgevec ], [True]*8)
        lapl=nx.laplacian(G)
        tgev=[ dot(lv,dot(lapl,lv)) for lv in tgevec ]
        assert_true(sum([abs(c-d) for c,d in zip(tgev,tgeval)]) < 1e-9)
        tgev.sort()
        lev=list(eigenval(lapl))
        lev.sort()
        assert_true(sum([abs(c-d) for c,d in zip(tgev,lev)]) < 1e-9)
Example #3
0
    def test_eigenvectors(self):
        try:
            import numpy as N
            eigenval=N.linalg.eigvals
        except ImportError:
            raise SkipTest('NumPy not available.')

        cs='ddiiddid'
        G=nxt.threshold_graph(cs)
        (tgeval,tgevec)=nxt.eigenvectors(cs)
        dot=N.dot
        assert_equal([ abs(dot(lv,lv)-1.0)<1e-9 for lv in tgevec ], [True]*8)
        lapl=nx.laplacian(G)
        tgev=[ dot(lv,dot(lapl,lv)) for lv in tgevec ]
        assert_true(sum([abs(c-d) for c,d in zip(tgev,tgeval)]) < 1e-9)
        tgev.sort()
        lev=list(eigenval(lapl))
        lev.sort()
        assert_true(sum([abs(c-d) for c,d in zip(tgev,lev)]) < 1e-9)