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Hello, I am having weird problem with svd
routine in python. I am comparing eigenvector values from python and matlab. And they are giving different values. Actually,
they are same but python gives negative values of these numbers. This is my test program (I am dealing with 100x100 matrices)
with the array I used in matlab. from numpy import* a=zeros((10,10)) a=array([ [6,-1,-1,-1,-1,-1,-1,0,0,0], [-1,7,-1,-1,-1,-1,-1,-1,0,0], [-1,-1,7,-1,-1,-1,-1,-1,0,0], [-1,-1,-1,6,-1,-1,-1,0,0,0], [-1,-1,-1,-1,6,-1,-1,0,0,0], [-1,-1,-1,-1,-1,8,-1,-1,-1,0], [-1,-1,-1,-1,-1,-1,9,-1,-1,-1], [0,-1,-1,0,0,-1,-1,6,-1,-1], [0,0,0,0,0,-1,-1,-1,4,-1], [0,0,0,0,0,0,-1,-1,-1,3]]) u,w,vt = linalg.svd(a) print u Output: u array([[
-1.05409255e-01,
1.48045079e-01,
-2.22322513e-01,
3.54544091e-15,
3.70413913e-01,
-7.27640158e-01,
2.60327955e-01,
1.08243955e-01,
-2.67189407e-01,
3.16227766e-01], [ -1.05409255e-01, 8.51968962e-02, 5.37745352e-01,
7.07106781e-01,
4.44089210e-16,
3.88578059e-15,
-2.31331268e-01,
4.16676907e-02,
-1.92898838e-01,
3.16227766e-01], [ -1.05409255e-01, 8.51968962e-02, 5.37745352e-01,
-7.07106781e-01,
-1.06858966e-15,
-3.05311332e-15,
-2.31331268e-01,
4.16676907e-02,
-1.92898838e-01,
3.16227766e-01], [ -1.05409255e-01, 1.48045079e-01, -2.22322513e-01,
-3.52416288e-15,
4.44947906e-01,
6.84607937e-01,
2.60327955e-01,
1.08243955e-01,
-2.67189407e-01,
3.16227766e-01], [ -1.05409255e-01, 1.48045079e-01, -2.22322513e-01,
1.16652940e-15,
-8.15361818e-01,
4.30322209e-02,
2.60327955e-01,
1.08243955e-01,
-2.67189407e-01,
3.16227766e-01], [ -1.05409255e-01,
-9.20330077e-01,
-1.07260256e-01,
1.88817436e-15,
1.11022302e-16,
-3.33066907e-16,
-4.57953818e-02,
-1.32746681e-01,
-1.03236512e-01,
3.16227766e-01], [ 9.48683298e-01, 7.14706072e-16, -1.04777298e-15,
3.61617704e-16,
-8.32667268e-17,
-1.52655666e-16,
-2.08166817e-16,
-9.36750677e-17,
1.42247325e-16,
3.16227766e-01], [ -1.05409255e-01, 2.15015734e-01, -4.92200980e-01,
-1.55431223e-15,
4.85722573e-16,
-2.77555756e-16,
-7.46027799e-01,
-1.27670308e-01,
1.65946178e-01,
3.16227766e-01], [ -1.05409255e-01, 1.51153561e-01, 1.21762878e-01,
1.66533454e-15,
1.80411242e-16,
3.46944695e-16, 3.33969907e-01, -7.50787335e-01, 4.19520882e-01,
3.16227766e-01], [ -1.05409255e-01,
-6.03682488e-02,
6.91751920e-02,
-1.23512311e-15,
-2.28983499e-16,
2.08166817e-17,
1.39531945e-01,
6.03137078e-01,
7.05135347e-01,
3.16227766e-01]]) Matlab output: u =
0.1054 -0.1480 0.2223 -0.0000 0.0000 0.8165 0.2603 0.1082 -0.2672 0.3162
0.1054 -0.0852 -0.5377 0.7071 -0.0000 -0.0000 -0.2313 0.0417 -0.1929 0.3162
0.1054 -0.0852 -0.5377 -0.7071 0.0000 -0.0000 -0.2313 0.0417 -0.1929 0.3162
0.1054 -0.1480 0.2223 -0.0000 -0.7071 -0.4082 0.2603 0.1082 -0.2672 0.3162
0.1054 -0.1480 0.2223 0.0000 0.7071 -0.4082 0.2603 0.1082 -0.2672 0.3162
0.1054
0.9203
0.1073 0.0000 0.0000 -0.0000 -0.0458 -0.1327 -0.1032 0.3162
-0.9487
0.0000 -0.0000 0.0000 -0.0000 -0.0000 -0.0000 0.0000 0.0000 0.3162
0.1054 -0.2150 0.4922 0.0000 0.0000 0.0000 -0.7460 -0.1277 0.1659 0.3162
0.1054 -0.1512 -0.1218 -0.0000 -0.0000 -0.0000 0.3340 -0.7508 0.4195 0.3162 0.1054 0.0604 -0.0692 0.0000 0.0000 -0.0000 0.1395 0.6031 0.7051 0.3162 I am not sure if svd in numpy has a problem or not. When I test this matrix in matlab, eigenvector values are different, Any idea why I am not getting exact results from both
program? Any input will be appreciated. Best, Nevin |
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