Matrix diagonalization
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Background:
If a
square matrix (
A), a number (λ), and a
vector (
v) are related by the equation
Av = λ
v, then λ and
v are said to be an
eigenvalue and eigenvector respectively of
A. An
n x
n matrix that is
symmetric (like most of significance) has
n eigenvalues, each corresponding to an eigenvector that points in a direction perpendicular to the other (
n - 1) eigenvectors. Many calculations involving a matrix can be done easily - if at all - only after first calculating its eigenvectors and eigenvalues, a process often called
diagonalization. This API diagonalizes symmetric matrices using the
Jacobi method.
Instructions:
After the url above you should type
/ followed by a comma-separated list of the
column vectors, none of which includes elements in the
lower-triangular portion of the matrix. Each column vector is a parenthesis-wrapped comma-separated list of numbers. If you want the results in json instead of html, snuggle
/api immediately after
...heroku.com
Example: Click here for the url ...herokuapp.com/
(1),(2,3),(4,5,6), which represents a simple symmetric 3x3 matrix. Note that the last number (1, 3, or 6) in each column vector is on the matrix's
diagonal.
Here are some unrelated webpages that also calculate eigenvalues and eigenvectors:
creator:
Peter Knipp
repo:
https://github.com/pknipp/eigen