Difference between revisions of "ApCoCoA-1:Num.EigenValuesAndVectors"
| Line 1: | Line 1: | ||
<command> | <command> | ||
<title>Num.EigenValuesAndVectors</title> | <title>Num.EigenValuesAndVectors</title> | ||
| − | <short_description>Computes the eigenvalues and eigenvectors of a matrix</short_description> | + | <short_description>Computes the eigenvalues and eigenvectors of a matrix.</short_description> |
<syntax> | <syntax> | ||
Num.EigenValuesAndVectors(A:Matrix):[B:Matrix, C:Matrix, D:Matrix] | Num.EigenValuesAndVectors(A:Matrix):[B:Matrix, C:Matrix, D:Matrix] | ||
Revision as of 14:21, 28 April 2009
Num.EigenValuesAndVectors
Computes the eigenvalues and eigenvectors of a matrix.
Syntax
Num.EigenValuesAndVectors(A:Matrix):[B:Matrix, C:Matrix, D:Matrix]
Description
Please note: The function(s) explained on this page is/are using the ApCoCoAServer. You will have to start the ApCoCoAServer in order to use it/them.
This function returns a list of three matrices, containing numerical approximation to the eigenvalues of A and (right hand) eigenvectors.
@param A A square matrix with rational entries.
@return The output [B:Matrix, C:Matrix, D:Matrix] contains a matrix B, where each column contains one of A's eigenvalues. The first row contains the eigenvalue's real part, the second row the imaginary. The matrices C and D both have the same dimensions as A. Column j of matrix C contains the real part of the eigenvector corresponding to eigenvalue j and column j of matrix D contains the imaginary part of the eigenvector correspsonding to eigenvalue j.
To compute only the left hand eigenvectors apply this method to the transposed matrix of A (see Transposed).
Example
A:=Mat([[1,2,7,18],[2,4,9,12],[23,8,9,10],[7,5,3,2]]); Dec(Num.EigenValuesAndVectors(A),3); -- CoCoAServer: computing Cpu Time = 0.016 ------------------------------- [Mat([ [<quotes>28.970</quotes>, <quotes>-13.677</quotes>, <quotes>0.353</quotes>, <quotes>0.353</quotes>], [<quotes>0</quotes>, <quotes>0</quotes>, <quotes>3.051</quotes>, <quotes>-3.051</quotes>] ]), Mat([ [<quotes>0.394</quotes>, <quotes>-0.581</quotes>, <quotes>0.260</quotes>, <quotes>0.260</quotes>], [<quotes>0.435</quotes>, <quotes>-0.442</quotes>, <quotes>-0.547</quotes>, <quotes>-0.547</quotes>], [<quotes>0.763</quotes>, <quotes>0.621</quotes>, <quotes>0</quotes>, <quotes>0</quotes>], [<quotes>0.268</quotes>, <quotes>0.281</quotes>, <quotes>0.046</quotes>, <quotes>0.046</quotes>] ]), Mat([ [<quotes>0</quotes>, <quotes>0</quotes>, <quotes>-0.031</quotes>, <quotes>0.031</quotes>], [<quotes>0</quotes>, <quotes>0</quotes>, <quotes>-0.301</quotes>, <quotes>0.301</quotes>], [<quotes>0</quotes>, <quotes>0</quotes>, <quotes>0.680</quotes>, <quotes>-0.680</quotes>], [<quotes>0</quotes>, <quotes>0</quotes>, <quotes>-0.274</quotes>, <quotes>0.274</quotes>] ])] --------------------------------------------------------------
See also
