이 질문을 팔로우합니다.
- 팔로우하는 게시물 피드에서 업데이트를 확인할 수 있습니다.
- 정보 수신 기본 설정에 따라 이메일을 받을 수 있습니다.
Errors in using null command due to truncation error
조회 수: 5 (최근 30일)
이전 댓글 표시
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{:});
답변 (1개)
Walter Roberson
2023년 8월 17일
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.
댓글 수: 6
Walter Roberson
2023년 8월 17일
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
2023년 8월 17일
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
2023년 8월 18일
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
2023년 8월 18일
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
2023년 8월 18일
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
참고 항목
카테고리
Help Center 및 File Exchange에서 Linear Algebra에 대해 자세히 알아보기
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!오류 발생
페이지가 변경되었기 때문에 동작을 완료할 수 없습니다. 업데이트된 상태를 보려면 페이지를 다시 불러오십시오.
웹사이트 선택
번역된 콘텐츠를 보고 지역별 이벤트와 혜택을 살펴보려면 웹사이트를 선택하십시오. 현재 계신 지역에 따라 다음 웹사이트를 권장합니다:
또한 다음 목록에서 웹사이트를 선택하실 수도 있습니다.
사이트 성능 최적화 방법
최고의 사이트 성능을 위해 중국 사이트(중국어 또는 영어)를 선택하십시오. 현재 계신 지역에서는 다른 국가의 MathWorks 사이트 방문이 최적화되지 않았습니다.
미주
- América Latina (Español)
- Canada (English)
- United States (English)
유럽
- 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)
아시아 태평양
- Australia (English)
- India (English)
- New Zealand (English)
- 中国
- 日本Japanese (日本語)
- 한국Korean (한국어)
