Errors in using null command due to truncation error
3 次查看(过去 30 天)
显示 更早的评论
Hi,
I'm trying to find eigenvectors of a 9-by-9 square matrix, corresponding to its eigenvalues. The matrix consists of components with complex numbers and one symbolic 'a', so I found nine eigenvalues ('a'), via solving the determinant of the matrix. For some eigenvalues, I used the 'vpa' command since, without 'vpa', they are obtained as a form of 'root(eqn, z, integer)'. Here the issue seems to arise. Due to the truncation error, the 'null' shows empty eigenvectors corresponding to the eigenvalues. FYI, I don't know how to assign a specific variable in 'eig' and it takes forever to run. Is there a breakthrough other than Gauss elimination method with suppressing close-to-zero values?
clc;
close all;
clear;
syms a
R = 0.5234;
r = 0.0054;
s = 0.0084;
for p = 1:3
M = [a*R*r 1i*r 0 0 0 0 a*R*8.78+1i*(8.78-p*R) 0 0;
0 0 a*R*s 1i*s 0 0 0 a*R*79.88+1i*(79.88-p*R) 0;
0 0 0 0 a*R*0.4542 1i*0.4542 -(a*R*291.06+1i*(291.06+p*R)) -(a*R*291.06+1i*(291.06+p*R)) 0;
a*R*8.78+1i*(8.78-p*R) 0 0 0 0 0 0 0 a*R;
0 a*R*8.78+1i*(8.78-p*R) 0 0 0 0 0 0 1i;
0 0 a*R*79.88+1i*(79.88-p*R) 0 0 0 0 0 a*R;
0 0 0 a*R*79.88+1i*(79.88-p*R) 0 0 0 0 1i;
0 0 0 0 a*R*291.06+1i*(291.06+p*R) 0 0 0 a*R;
0 0 0 0 0 a*R*291.06+1i*(291.06+p*R) 0 0 1i];
Det = det(M);
DetEqn = Det == 0;
EigenVal1 = solve(DetEqn,a);
EigVal = vpa(EigenVal1);
for j=1:rank(M)
M_temp = subs(M,a,EigVal(j));
EigVec(:,j) = null(M_temp)
end
end
Unable to perform assignment because the indices on the left side are not compatible with the size of the right side.
Error in sym/privsubsasgn (line 1168)
L_tilde2 = builtin('subsasgn',L_tilde,struct('type','()','subs',{varargin}),R_tilde);
Error in indexing (line 999)
C = privsubsasgn(L,R,inds{:});
回答(1 个)
Walter Roberson
2023-8-17
Your code assumes that the null space is the same size each time, but most of the time the null space is empty. You cannot store an empty vector into a definite vector location.
You need to decide what you want to do when the null space is empty.
6 个评论
Walter Roberson
2023-8-17
syms a
R = 0.5234;
r = 0.0054;
s = 0.0084;
for p = 1:3
M = [a*R*r 1i*r 0 0 0 0 a*R*8.78+1i*(8.78-p*R) 0 0;
0 0 a*R*s 1i*s 0 0 0 a*R*79.88+1i*(79.88-p*R) 0;
0 0 0 0 a*R*0.4542 1i*0.4542 -(a*R*291.06+1i*(291.06+p*R)) -(a*R*291.06+1i*(291.06+p*R)) 0;
a*R*8.78+1i*(8.78-p*R) 0 0 0 0 0 0 0 a*R;
0 a*R*8.78+1i*(8.78-p*R) 0 0 0 0 0 0 1i;
0 0 a*R*79.88+1i*(79.88-p*R) 0 0 0 0 0 a*R;
0 0 0 a*R*79.88+1i*(79.88-p*R) 0 0 0 0 1i;
0 0 0 0 a*R*291.06+1i*(291.06+p*R) 0 0 0 a*R;
0 0 0 0 0 a*R*291.06+1i*(291.06+p*R) 0 0 1i];
Det = det(M);
DetEqn = Det == 0;
EigenVal1 = solve(DetEqn,a);
EigVal = (EigenVal1);
for j=1:rank(M)
M_temp = subs(M,a,EigVal(j));
EV = null(M_temp);
if isempty(EV)
EigVec(:,j,p) = sym(NaN(size(EV,1),1));
else
EigVec(:,j,p) = EV;
end
end
end
format long g
EigVec = double(EigVec)
EigVec =
EigVec(:,:,1) =
Columns 1 through 3
-0.0604434080666857 - 0.0568402099138265i -0.0604434080666857 + 0.0568402099138265i 0 + 0i
-0.0568402099138265 + 0.0604434080666857i -0.0568402099138265 - 0.0604434080666857i 0 + 0i
-0.00630053702136478 - 0.00625925383312013i -0.00630053702136478 + 0.00625925383312013i 0 + 0i
-0.00625925383312013 + 0.00630053702136478i -0.00625925383312013 - 0.00630053702136478i 0 + 0i
-0.00171477249055503 - 0.00171785608816912i -0.00171477249055503 + 0.00171785608816912i 0.998204973259795 + 0i
-0.00171785608816912 + 0.00171477249055503i -0.00171785608816912 - 0.00171477249055503i 1 + 0i
0 + 0i 0 + 0i 0 + 0i
0 + 0i 0 + 0i 0 + 0i
1 + 0i 1 + 0i 0 + 0i
Columns 4 through 6
0 + 0i 1.06339171087373 + 0i NaN + 0i
0 + 0i 1 + 0i NaN + 0i
1.00659554466799 + 0i 0 + 0i NaN + 0i
1 + 0i 0 + 0i NaN + 0i
0 + 0i 0 + 0i NaN + 0i
0 + 0i 0 + 0i NaN + 0i
0 + 0i 0 + 0i NaN + 0i
0 + 0i 0 + 0i NaN + 0i
0 + 0i 0 + 0i NaN + 0i
Columns 7 through 9
NaN + 0i NaN + 0i NaN + 0i
NaN + 0i NaN + 0i NaN + 0i
NaN + 0i NaN + 0i NaN + 0i
NaN + 0i NaN + 0i NaN + 0i
NaN + 0i NaN + 0i NaN + 0i
NaN + 0i NaN + 0i NaN + 0i
NaN + 0i NaN + 0i NaN + 0i
NaN + 0i NaN + 0i NaN + 0i
NaN + 0i NaN + 0i NaN + 0i
EigVec(:,:,2) =
Columns 1 through 3
-0.0641387232677706 - 0.0564917511132487i -0.0641387232677706 + 0.0564917511132487i 0 + 0i
-0.0564917511132487 + 0.0641387232677706i -0.0564917511132487 - 0.0641387232677706i 0 + 0i
-0.00634195365255762 - 0.00625884452532305i -0.00634195365255762 + 0.00625884452532305i 0 + 0i
-0.00625884452532305 + 0.00634195365255762i -0.00625884452532305 - 0.00634195365255762i 0 + 0i
-0.00171169167540565 - 0.00171784779045346i -0.00171169167540565 + 0.00171784779045346i 0.996416379214725 + 0i
-0.00171784779045346 + 0.00171169167540565i -0.00171784779045346 - 0.00171169167540565i 1 + 0i
0 + 0i 0 + 0i 0 + 0i
0 + 0i 0 + 0i 0 + 0i
1 + 0i 1 + 0i 0 + 0i
Columns 4 through 6
0 + 0i 1.13536440283453 + 0i NaN + 0i
0 + 0i 1 + 0i NaN + 0i
1.0132786693931 + 0i 0 + 0i NaN + 0i
1 + 0i 0 + 0i NaN + 0i
0 + 0i 0 + 0i NaN + 0i
0 + 0i 0 + 0i NaN + 0i
0 + 0i 0 + 0i NaN + 0i
0 + 0i 0 + 0i NaN + 0i
0 + 0i 0 + 0i NaN + 0i
Columns 7 through 9
NaN + 0i NaN + 0i NaN + 0i
NaN + 0i NaN + 0i NaN + 0i
NaN + 0i NaN + 0i NaN + 0i
NaN + 0i NaN + 0i NaN + 0i
NaN + 0i NaN + 0i NaN + 0i
NaN + 0i NaN + 0i NaN + 0i
NaN + 0i NaN + 0i NaN + 0i
NaN + 0i NaN + 0i NaN + 0i
NaN + 0i NaN + 0i NaN + 0i
EigVec(:,:,3) =
Columns 1 through 3
-0.0680253050205014 - 0.0558597772365388i -0.0680253050205014 + 0.0558597772365388i 0 + 0i
-0.0558597772365388 + 0.0680253050205014i -0.0558597772365388 - 0.0680253050205014i 0 + 0i
-0.00638363887049742 - 0.00625815577392186i -0.00638363887049742 + 0.00625815577392186i 0 + 0i
-0.00625815577392186 + 0.00638363887049742i -0.00625815577392186 - 0.00638363887049742i 0 + 0i
-0.0017086164151074 - 0.00171783399737567i -0.0017086164151074 + 0.00171783399737567i 0.99463418334813 + 0i
-0.00171783399737567 + 0.0017086164151074i -0.00171783399737567 - 0.0017086164151074i 1 + 0i
0 + 0i 0 + 0i 0 + 0i
0 + 0i 0 + 0i 0 + 0i
1 + 0i 1 + 0i 0 + 0i
Columns 4 through 6
0 + 0i 1.21778690116231 + 0i NaN + 0i
0 + 0i 1 + 0i NaN + 0i
1.02005113025445 + 0i 0 + 0i NaN + 0i
1 + 0i 0 + 0i NaN + 0i
0 + 0i 0 + 0i NaN + 0i
0 + 0i 0 + 0i NaN + 0i
0 + 0i 0 + 0i NaN + 0i
0 + 0i 0 + 0i NaN + 0i
0 + 0i 0 + 0i NaN + 0i
Columns 7 through 9
NaN + 0i NaN + 0i NaN + 0i
NaN + 0i NaN + 0i NaN + 0i
NaN + 0i NaN + 0i NaN + 0i
NaN + 0i NaN + 0i NaN + 0i
NaN + 0i NaN + 0i NaN + 0i
NaN + 0i NaN + 0i NaN + 0i
NaN + 0i NaN + 0i NaN + 0i
NaN + 0i NaN + 0i NaN + 0i
NaN + 0i NaN + 0i NaN + 0i
Walter Roberson
2023-8-17
Note that in this above code, the null() calculation is working on the symbolic solutions, so there is no truncation error going on.
Seung Hyeop Hyun
2023-8-18
Walter,
Thank you for leaving your comments. The issue here is that there must be eigenvectors corresponding to the eigenvalues, which can be obtained from the 'null', and also the dimension of the eigenvectors is definitely 9x1. The 'null' cannot find the eigenvectors and provides 0X1 empty vectors. I believe that it's because of the approximation due to using 'vpa'. The 'a' is already replaced by one of eigenvalues, and therefore, the null is not working on the symbolic solutions. Alternatively, I can do 'eig' for M after one of eigenvalues is entered.
Torsten
2023-8-18
I don't know why you talk about "eigenvalues", but I agree that if "a" gives det(M(a)) = 0, null(M(a)) should be at least 1-dimensional and not empty.
Walter Roberson
2023-8-18
You did not take into account that you use floating point constants and that some of the calculations take place in floating point instead of as symbolic numbers.
When you use symbolic numbers consistently then the problem does not show up.
Q = @(v) sym(v);
syms a
R = Q(5234)/Q(10)^4;
r = Q(54)/Q(10)^4;
s = Q(84)/Q(10)^4;
n8_78 = Q(878)/Q(10)^2;
n79_88 = Q(7988)/Q(10)^2;
n_4542 = Q(4542)/Q(10)^4;
n291_06 = Q(29106)/Q(10)^2;
for p = 1:3
M = [a*R*r 1i*r 0 0 0 0 a*R*n8_78+1i*(n8_78-p*R) 0 0;
0 0 a*R*s 1i*s 0 0 0 a*R*n79_88+1i*(n79_88-p*R) 0;
0 0 0 0 a*R*n_4542 1i*n_4542 -(a*R*n291_06+1i*(n291_06+p*R)) -(a*R*n291_06+1i*(n291_06+p*R)) 0;
a*R*n8_78+1i*(n8_78-p*R) 0 0 0 0 0 0 0 a*R;
0 a*R*n8_78+1i*(n8_78-p*R) 0 0 0 0 0 0 1i;
0 0 a*R*n79_88+1i*(n79_88-p*R) 0 0 0 0 0 a*R;
0 0 0 a*R*n79_88+1i*(n79_88-p*R) 0 0 0 0 1i;
0 0 0 0 a*R*n291_06+1i*(n291_06+p*R) 0 0 0 a*R;
0 0 0 0 0 a*R*n291_06+1i*(n291_06+p*R) 0 0 1i];
Det = det(M);
DetEqn = Det == 0;
EigenVal1 = solve(DetEqn,a);
EigVal = EigenVal1;
for j=1:rank(M)
M_temp = subs(M,a,EigVal(j));
EV = null(M_temp);
if isempty(EV)
EigVec(:,j,p) = sym(NaN(size(EV,1),1));
else
EigVec(:,j,p) = EV;
end
end
end
EigVec
EigVec(:,:,1) =

EigVec(:,:,2) =

EigVec(:,:,3) =

format long g
EigVec = double(EigVec)
EigVec =
EigVec(:,:,1) =
Columns 1 through 3
-0.0604434080666857 - 0.0568402099138265i -0.0604434080666857 + 0.0568402099138265i 0 + 0i
-0.0568402099138265 + 0.0604434080666857i -0.0568402099138265 - 0.0604434080666857i 0 + 0i
-0.00630053702136478 - 0.00625925383312013i -0.00630053702136478 + 0.00625925383312013i 0 + 0i
-0.00625925383312013 + 0.00630053702136478i -0.00625925383312013 - 0.00630053702136478i 0 + 0i
-0.00171477249055503 - 0.00171785608816912i -0.00171477249055503 + 0.00171785608816912i 0.998204973259795 + 0i
-0.00171785608816912 + 0.00171477249055503i -0.00171785608816912 - 0.00171477249055503i 1 + 0i
0 + 0i 0 + 0i 0 + 0i
0 + 0i 0 + 0i 0 + 0i
1 + 0i 1 + 0i 0 + 0i
Columns 4 through 6
0 + 0i 1.06339171087373 + 0i -2.07917517265388 - 0.12335357734933i
0 + 0i 1 + 0i 2.08986241502569 + 0.131173171659899i
1.00659554466799 + 0i 0 + 0i -1.17431482491886 - 3.23249177899391i
1 + 0i 0 + 0i 1.16945872447306 + 3.25381182291119i
0 + 0i 0 + 0i 0.389692214298109 - 0.187973926292369i
0 + 0i 0 + 0i -0.392422256869245 + 0.187636508068213i
0 + 0i 0 + 0i 0.0467535877540691 + 0.00573056182938062i
0 + 0i 0 + 0i -0.15363302189684 + 0.127699515578846i
0 + 0i 0 + 0i 1 + 0i
Columns 7 through 9
-2.07917517265388 + 0.12335357734933i -1.91125259969198 - 0.520193365405037i -1.91125259969198 + 0.520193365405037i
2.08986241502569 - 0.131173171659899i 1.91129494286941 + 0.553169312823223i 1.91129494286941 - 0.553169312823223i
-1.17431482491886 + 3.23249177899391i -0.105661537118353 - 0.770245234313409i -0.105661537118353 + 0.770245234313409i
1.16945872447306 - 3.25381182291119i 0.0937570861782642 + 0.775325421161631i 0.0937570861782642 - 0.775325421161631i
0.389692214298109 + 0.187973926292369i 0.0716575680173222 - 0.185960430138347i 0.0716575680173222 + 0.185960430138347i
-0.392422256869245 - 0.187636508068213i -0.0749584912828433 + 0.185626626193629i -0.0749584912828433 - 0.185626626193629i
0.0467535877540691 - 0.00573056182938062i 0.0363384221349967 + 0.0221560988269227i 0.0363384221349967 - 0.0221560988269227i
-0.15363302189684 - 0.127699515578846i -0.00986540081559587 + 0.00258850280209401i -0.00986540081559587 - 0.00258850280209401i
1 + 0i 1 + 0i 1 + 0i
EigVec(:,:,2) =
Columns 1 through 3
-0.0641387232677706 - 0.0564917511132487i -0.0641387232677706 + 0.0564917511132487i 0 + 0i
-0.0564917511132487 + 0.0641387232677706i -0.0564917511132487 - 0.0641387232677706i 0 + 0i
-0.00634195365255762 - 0.00625884452532305i -0.00634195365255762 + 0.00625884452532305i 0 + 0i
-0.00625884452532305 + 0.00634195365255762i -0.00625884452532305 - 0.00634195365255762i 0 + 0i
-0.00171169167540565 - 0.00171784779045346i -0.00171169167540565 + 0.00171784779045346i 0.996416379214726 + 0i
-0.00171784779045346 + 0.00171169167540565i -0.00171784779045346 - 0.00171169167540565i 1 + 0i
0 + 0i 0 + 0i 0 + 0i
0 + 0i 0 + 0i 0 + 0i
1 + 0i 1 + 0i 0 + 0i
Columns 4 through 6
0 + 0i 1.13536440283453 + 0i -1.03424396514104 - 0.0577669915193808i
0 + 0i 1 + 0i 1.04493120751284 + 0.0655865858299493i
1.0132786693931 + 0i 0 + 0i -0.589585462682334 - 1.60558586753832i
1 + 0i 0 + 0i 0.58472936223653 + 1.62690591145559i
0 + 0i 0 + 0i 0.193481085863487 - 0.0941556722582628i
0 + 0i 0 + 0i -0.196211128434622 + 0.0938182540341066i
0 + 0i 0 + 0i 0.0116310771845003 + 0.00138540923306503i
0 + 0i 0 + 0i -0.0380957587743605 + 0.0318852196758995i
0 + 0i 0 + 0i 1 + 0i
Columns 7 through 9
-1.03424396514104 + 0.0577669915193808i -0.955605128257274 - 0.243608708993425i -0.955605128257274 + 0.243608708993425i
1.04493120751284 - 0.0655865858299493i 0.955647471434705 + 0.276584656411611i 0.955647471434705 - 0.276584656411611i
-0.589585462682334 + 1.60558586753832i -0.058782994029221 - 0.382582523732593i -0.058782994029221 + 0.382582523732593i
0.58472936223653 - 1.62690591145559i 0.0468785430891321 + 0.387662710580816i 0.0468785430891321 - 0.387662710580816i
0.193481085863487 + 0.0941556722582628i 0.0341783223759006 - 0.0931471170415329i 0.0341783223759006 + 0.0931471170415329i
-0.196211128434622 - 0.0938182540341066i -0.0374792456414217 + 0.0928133130968145i -0.0374792456414217 - 0.0928133130968145i
0.0116310771845003 - 0.00138540923306503i 0.00912923446797742 + 0.00536880051870816i 0.00912923446797742 - 0.00536880051870816i
-0.0380957587743605 - 0.0318852196758995i -0.00244438930219064 + 0.000683128476076533i -0.00244438930219064 - 0.000683128476076533i
1 + 0i 1 + 0i 1 + 0i
EigVec(:,:,3) =
Columns 1 through 3
-0.0680253050205014 - 0.0558597772365388i -0.0680253050205014 + 0.0558597772365388i 0 + 0i
-0.0558597772365388 + 0.0680253050205014i -0.0558597772365388 - 0.0680253050205014i 0 + 0i
-0.00638363887049742 - 0.00625815577392186i -0.00638363887049742 + 0.00625815577392186i 0 + 0i
-0.00625815577392186 + 0.00638363887049742i -0.00625815577392186 - 0.00638363887049742i 0 + 0i
-0.0017086164151074 - 0.00171783399737567i -0.0017086164151074 + 0.00171783399737567i 0.99463418334813 + 0i
-0.00171783399737567 + 0.0017086164151074i -0.00171783399737567 - 0.0017086164151074i 1 + 0i
0 + 0i 0 + 0i 0 + 0i
0 + 0i 0 + 0i 0 + 0i
1 + 0i 1 + 0i 0 + 0i
Columns 4 through 6
0 + 0i 1.21778690116231 + 0i -0.685933562636758 - 0.0359047962427311i
0 + 0i 1 + 0i 0.696620805008562 + 0.0437243905532995i
1.02005113025445 + 0i 0 + 0i -0.394675675270157 - 1.06328389705312i
1 + 0i 0 + 0i 0.389819574824353 + 1.0846039409704i
0 + 0i 0 + 0i 0.12807737638528 - 0.0628829209135606i
0 + 0i 0 + 0i -0.130807418956415 + 0.0625455026894044i
0 + 0i 0 + 0i 0.00514395587663915 + 0.000594946349441334i
0 + 0i 0 + 0i -0.0167933653854523 + 0.0141531959048798i
0 + 0i 0 + 0i 1 + 0i
Columns 7 through 9
-0.685933562636758 + 0.0359047962427311i -0.637055971112372 - 0.151413823522888i -0.637055971112372 + 0.151413823522888i
0.696620805008562 - 0.0437243905532995i 0.637098314289803 + 0.184389770941074i 0.637098314289803 - 0.184389770941074i
-0.394675675270157 + 1.06328389705312i -0.0431568129995103 - 0.253361620205655i -0.0431568129995103 + 0.253361620205655i
0.389819574824353 - 1.0846039409704i 0.0312523620594214 + 0.258441807053877i 0.0312523620594214 - 0.258441807053877i
0.12807737638528 + 0.0628829209135606i 0.0216852404954267 - 0.0622093460092614i 0.0216852404954267 + 0.0622093460092614i
-0.130807418956415 - 0.0625455026894044i -0.0249861637609478 + 0.061875542064543i -0.0249861637609478 - 0.061875542064543i
0.00514395587663915 - 0.000594946349441334i 0.0040759677296243 + 0.00231048172032896i 0.0040759677296243 - 0.00231048172032896i
-0.0167933653854523 - 0.0141531959048798i -0.0010764184837051 + 0.000319388109428762i -0.0010764184837051 - 0.000319388109428762i
1 + 0i 1 + 0i 1 + 0i
另请参阅
类别
在 Help Center 和 File Exchange 中查找有关 Linear Algebra 的更多信息
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!发生错误
由于页面发生更改,无法完成操作。请重新加载页面以查看其更新后的状态。
您也可以从以下列表中选择网站:
如何获得最佳网站性能
选择中国网站(中文或英文)以获得最佳网站性能。其他 MathWorks 国家/地区网站并未针对您所在位置的访问进行优化。
美洲
- América Latina (Español)
- Canada (English)
- United States (English)
欧洲
- Belgium (English)
- Denmark (English)
- Deutschland (Deutsch)
- España (Español)
- Finland (English)
- France (Français)
- Ireland (English)
- Italia (Italiano)
- Luxembourg (English)
- Netherlands (English)
- Norway (English)
- Österreich (Deutsch)
- Portugal (English)
- Sweden (English)
- Switzerland
- United Kingdom(English)
亚太
- Australia (English)
- India (English)
- New Zealand (English)
- 中国
- 日本Japanese (日本語)
- 한국Korean (한국어)
