edit file...

ext opens the specified text file.
edit class/fun, edit private/fun, or edit class/private/fun can be
used to edit a method, private function, or private method (for the class named
class).
Remarks
To specify the default editor for MATLAB, select Preferences from the File menu. On the Editor/Debugger panel, select MATLAB’s Editor/Debugger or
specify another.
UNIX Users
If you run MATLAB with the -nodisplay startup option, or run without the
DISPLAY environment variable set, edit uses the External Editor command.
It does not use the MATLAB Editor/Debugger, but instead uses the default
editor defined for your system in $matlabroot/X11/app-defaults/Matlab.
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edit
You can specify the editor that the edit function uses or specify editor options
by adding the following line to your own .Xdefaults file, located in ~home.
matlab*externalEditorCommand: $EDITOR -option $FILE
where:
• $EDITOR is the name of your default editor, for example, emacs; leaving it as $EDITOR means your default system editor will be used.
• -option is an option flag for the specified editor.
• $FILE means the filename you type with the edit command will open in the
specified editor.
Then, before starting MATLAB, run
xrdb -merge ~home/.Xdefaults
For the HP 700 platform, the default editor is instead defined in $matlabroot/
toolbox/matlab/general/edit.m. To change it, open the file edit.m and edit
the line
eval( ['!$EDITOR “' file '" &']);
See Also
open, type
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eig
2eig
Purpose
Find eigenvalues and eigenvectors
Syntax
d = eig(A)
d = eig(A,B)
[V,D] = eig(A)
[V,D] = eig(A,'nobalance')
[V,D] = eig(A,B)
[V,D] = eig(A,B,flag)
Description
d = eig(A) returns a vector of the eigenvalues of matrix A.
Note If S is sparse and symmetric, you can use d = eig(S) to returns the
eigenvalues of S. To request eigenvectors, and in all other cases, use eigs to
find the eigenvalues or eigenvectors of sparse matrices.
d = eig(A,B) returns a vector containing the generalized eigenvalues, if A and
B are square matrices.
[V,D] = eig(A) produces matrices of eigenvalues (D) and eigenvectors (V) of
matrix A, so that A*V = V*D. Matrix D is the canonical form of A—a diagonal matrix with A’s eigenvalues on the main diagonal. Matrix V is the modal
matrix—its columns are the eigenvectors of A.
For eig(A), the eigenvectors are scaled so that the norm of each is 1.0.
If W is a matrix such that W'*A = D*W', the columns of W are the left eigenvectors of A . Use [W,D] = eig(A.'); W = conj(W) to compute the left eigenvectors.
[V,D] = eig(A,'nobalance') finds eigenvalues and eigenvectors without a
preliminary balancing step. Ordinarily, balancing improves the conditioning of
the input matrix, enabling more accurate computation of the eigenvectors and
eigenvalues. However, if a matrix contains small elements that are really due
to roundoff error, balancing may scale them up to make them as significant as
the other elements of the original matrix, leading to incorrect eigenvectors. Use
the nobalance option in this event. See the balance function for more details.
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eig
[V,D] = eig(A,B) produces a diagonal matrix D of generalized eigenvalues
and a full matrix V whose columns are the corresponding eigenvectors so that
A*V = B*V*D.
[V,D] = eig(A,B,flag) specifies the algorithm used to compute eigenvalues
and eigenvectors. flag can be:
'chol'
Computes the generalized eigenvalues of A and B using the
Cholesky factorization of B. This is the default for symmetric
(Hermitian) A and symmetric (Hermitian) positive definite B.
'qz'
Ignores the symmetry, if any, and uses the QZ algorithm as it
would for nonsymmetric (non-Hermitian) A and B.
Remarks
The eigenvalue problem is to determine the nontrivial solutions of the equation
Ax = λ x
where A is an n-by-n matrix, x is a length n column vector, and λ is a scalar.
The n values of λ that satisfy the equation are the eigenvalues, and the
corresponding values of x are the right eigenvectors. In MATLAB, the function eig solves for the eigenvalues λ , and optionally the eigenvectors x .