Status: New
Owner: ----
Labels: Type-Defect Priority-Medium
New issue 3971 by ryan.gre...@gmail.com: Missing eigenvalues
http://code.google.com/p/sympy/issues/detail?id=3971
When calculating eigenvalues for some matricies I'm working with I get
fewer than there should be. For example:
In [10]: W
Out[10]:
Matrix([
[0, 5/8, 3/8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 4/5, 1/5, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 1/3, 2/3, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 1/4, 0, 0, 3/4, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 1/2, 1/2, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 1/3, 0, 0, 0, 0, 2/3, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0],
[0, 0, 0, 0, 1/2, 0, 0, 0, 0, 0, 0, 1/2, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1],
[0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0]])
In [11]: W.eigenvals()
Out[11]: {0: 6, 1: 1}
In [12]: Wnp = np.array([[np.float(i) for i in row] for row in W.tolist()])
In [13]: np.linalg.eigvals(Wnp)
Out[13]:
array([ 0.00000000+0.j , 0.00000000+0.j ,
0.00000000+0.j , 0.00000000+0.j ,
0.00000000+0.j , 0.00000000+0.j ,
1.00000000+0.j , 0.64438276+0.69026752j,
0.64438276-0.69026752j, -0.13703613+0.86913433j,
-0.13703613-0.86913433j, -0.75734663+0.38822447j,
-0.75734663-0.38822447j])
In [14]: sympy.roots(W.charpoly())
Out[14]: {0: 6, 1: 1}
In [15]:
notice that I only get 7 eigenvalues from the 13x13 matrix. numpy reports
all 13. furthermore, I only get 7 roots from the characteristic polynomial.
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