Extract several matrices from single column vector

2 次查看（过去 30 天）
Cedric Kotitschke
Cedric Kotitschke 2023-10-24
回答： Cedric Kotitschke 2023-10-24
Hey,
I have three matrices
A, B, C, D which I flatten to a single column vector:
J = [A(:); B(:); C(:); D(:)]
How can I used indexing to extract the matrices again? Unfortunately, I cannot use reshape because J is a vector of realp objects.
Basically I want to do this:
A = J(idxA);
B = J(idxB);
C = J(idxC);
D = J(idxD);
Thanks for your help!
  6 个评论
显示 4更早的评论
Cedric Kotitschke
Cedric Kotitschke 2023-10-24
n = 20;
% Create genmat object
pGenmat = [];
for i = 1:n
pGenmat = [pGenmat; realp(sprintf('p%d', i), i)];
end
% Create double array with same size
pDouble = reshape(1:n, n, 1);
% Reshape double array (no error)
pDouble_reshaped = reshape(pDouble, 4, 5);
% Reshape genmat (error)
pGenmat_reshaped = reshape(pGenmat, 4, 5);

请先登录，再进行评论。

请先登录，再回答此问题。

采纳的回答

Cedric Kotitschke
Cedric Kotitschke 2023-10-24
For everyone who also struggles with this, here's my solution. It is clunky but that's only because genmat objects are buggy when it comes to reshaping and matrix indexing.
The input to this example are the parameterset, which holds names, values and nominal values of some parameters and the function handle which includes trimming and linearizing of a simulink model, given the parameterset.
% Utility function
function [J, sys] = getSys(x, parameterset, fun)
parameterset.Values = x;
sys = fun(parameterset);
J = [sys.A(:); sys.B(:); sys.C(:); sys.D(:)];
end
% Get nominal system
[J0, sys0] = getSys(parameterset.NominalValues, parameterset, fun);
% Compute jacobian
f = @(x) getSys(x, parameterset, fun);
x0 = parameterset.NominalValues;
jac = roughjacobianest(f, x0);
% Create tunable parameters
p = [];
for param = parameterset.Elements
p = [p; realp(param.Name, param.NominalValue)];
end
% Create linear system
J = J0 + jac * (p - parameterset.NominalValues(:));
% This workaround is necessary because both reshaping and proper
% indexing is buggy when it comes to genmat objects
na = numel(sys0.A);
szA = size(sys0.A);
Ja = J(1:na);
nb = numel(sys0.B);
szB = size(sys0.B);
Jb = J((na+1):(na+nb));
nc = numel(sys0.C);
szC = size(sys0.C);
Jc = J((na+nb+1):(na+nb+nc));
nd = numel(sys0.D);
szD = size(sys0.D);
Jd = J((na+nb+nc+1):(na+nb+nc+nd));
A = genmat(zeros(szA));
for i = 1:na
[idxRow, idxCol] = ind2sub(szA, i);
A(idxRow, idxCol) = Ja(i);
end
B = genmat(zeros(szB));
for i = 1:nb
[idxRow, idxCol] = ind2sub(szB, i);
B(idxRow, idxCol) = Jb(i);
end
C = genmat(zeros(szC));
for i = 1:nc
[idxRow, idxCol] = ind2sub(szC, i);
C(idxRow, idxCol) = Jc(i);
end
D = genmat(zeros(szD));
for i = 1:nd
[idxRow, idxCol] = ind2sub(szD, i);
D(idxRow, idxCol) = Jd(i);
end
sys = ss(A, B, C, D);

更多回答（0 个）

类别

在 Help Center 和 File Exchange 中查找有关 Time and Frequency Domain Analysis 的更多信息

标签

产品


版本

R2021a

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by