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@menu
* Functions and Variables for diag::
@end menu
@node Functions and Variables for diag, , diag, diag
@section Functions and Variables for diag
@deffn {Function} diag (@var{lm})
Constructs a square matrix with the matrices of @var{lm} in the diagonal. @var{lm} is a list of matrices or scalars.
Example:
@example
(%i1) load("diag")$
(%i2) a1:matrix([1,2,3],[0,4,5],[0,0,6])$
(%i3) a2:matrix([1,1],[1,0])$
(%i4) diag([a1,x,a2]);
[ 1 2 3 0 0 0 ]
[ ]
[ 0 4 5 0 0 0 ]
[ ]
[ 0 0 6 0 0 0 ]
(%o4) [ ]
[ 0 0 0 x 0 0 ]
[ ]
[ 0 0 0 0 1 1 ]
[ ]
[ 0 0 0 0 1 0 ]
@end example
To use this function write first @code{load("diag")}.
@opencatbox
@category{Matrices} @category{Share packages} @category{Package diag}
@closecatbox
@end deffn
@deffn {Function} JF (@var{lambda},@var{n})
Returns the Jordan cell of order @var{n} with eigenvalue @var{lambda}.
Example:
@example
(%i1) load("diag")$
(%i2) JF(2,5);
[ 2 1 0 0 0 ]
[ ]
[ 0 2 1 0 0 ]
[ ]
(%o2) [ 0 0 2 1 0 ]
[ ]
[ 0 0 0 2 1 ]
[ ]
[ 0 0 0 0 2 ]
(%i3) JF(3,2);
[ 3 1 ]
(%o3) [ ]
[ 0 3 ]
@end example
To use this function write first @code{load("diag")}.
@opencatbox
@category{Package diag}
@closecatbox
@end deffn
@deffn {Function} jordan (@var{mat})
Returns the Jordan form of matrix @var{mat}, but codified in a Maxima list.
To get the corresponding matrix, call function @code{dispJordan} using as argument
the output of @code{jordan}.
Example:
@example
(%i1) load("diag")$
(%i3) a:matrix([2,0,0,0,0,0,0,0],
[1,2,0,0,0,0,0,0],
[-4,1,2,0,0,0,0,0],
[2,0,0,2,0,0,0,0],
[-7,2,0,0,2,0,0,0],
[9,0,-2,0,1,2,0,0],
[-34,7,1,-2,-1,1,2,0],
[145,-17,-16,3,9,-2,0,3])$
(%i34) jordan(a);
(%o4) [[2, 3, 3, 1], [3, 1]]
(%i5) dispJordan(%);
[ 2 1 0 0 0 0 0 0 ]
[ ]
[ 0 2 1 0 0 0 0 0 ]
[ ]
[ 0 0 2 0 0 0 0 0 ]
[ ]
[ 0 0 0 2 1 0 0 0 ]
(%o5) [ ]
[ 0 0 0 0 2 1 0 0 ]
[ ]
[ 0 0 0 0 0 2 0 0 ]
[ ]
[ 0 0 0 0 0 0 2 0 ]
[ ]
[ 0 0 0 0 0 0 0 3 ]
@end example
To use this function write first @code{load("diag")}. See also @code{dispJordan} and @code{minimalPoly}.
@opencatbox
@category{Package diag}
@closecatbox
@end deffn
@deffn {Function} dispJordan (@var{l})
Returns the Jordan matrix associated to the codification given by the Maxima list @var{l}, which is the output given by function @code{jordan}.
Example:
@example
(%i1) load("diag")$
(%i2) b1:matrix([0,0,1,1,1],
[0,0,0,1,1],
[0,0,0,0,1],
[0,0,0,0,0],
[0,0,0,0,0])$
(%i3) jordan(b1);
(%o3) [[0, 3, 2]]
(%i4) dispJordan(%);
[ 0 1 0 0 0 ]
[ ]
[ 0 0 1 0 0 ]
[ ]
(%o4) [ 0 0 0 0 0 ]
[ ]
[ 0 0 0 0 1 ]
[ ]
[ 0 0 0 0 0 ]
@end example
To use this function write first @code{load("diag")}. See also @code{jordan} and @code{minimalPoly}.
@opencatbox
@category{Package diag}
@closecatbox
@end deffn
@deffn {Function} minimalPoly (@var{l})
Returns the minimal polynomial associated to the codification given by the Maxima list @var{l}, which is the output given by function @code{jordan}.
Example:
@example
(%i1) load("diag")$
(%i2) a:matrix([2,1,2,0],
[-2,2,1,2],
[-2,-1,-1,1],
[3,1,2,-1])$
(%i3) jordan(a);
(%o3) [[- 1, 1], [1, 3]]
(%i4) minimalPoly(%);
3
(%o4) (x - 1) (x + 1)
@end example
To use this function write first @code{load("diag")}. See also @code{jordan} and @code{dispJordan}.
@opencatbox
@category{Package diag}
@closecatbox
@end deffn
@deffn {Function} ModeMatrix (@var{A},@var{l})
Returns the matrix @var{M} such that @math{(M^^-1).A.M=J}, where @var{J} is the Jordan form of @var{A}. The Maxima list @var{l} is the codified form of the Jordan form as returned by function @code{jordan}.
Example:
@example
(%i1) load("diag")$
(%i2) a:matrix([2,1,2,0],
[-2,2,1,2],
[-2,-1,-1,1],
[3,1,2,-1])$
(%i3) jordan(a);
(%o3) [[- 1, 1], [1, 3]]
(%i4) M: ModeMatrix(a,%);
[ 1 - 1 1 1 ]
[ ]
[ 1 ]
[ - - - 1 0 0 ]
[ 9 ]
[ ]
(%o4) [ 13 ]
[ - -- 1 - 1 0 ]
[ 9 ]
[ ]
[ 17 ]
[ -- - 1 1 1 ]
[ 9 ]
(%i5) is( (M^^-1).a.M = dispJordan(%o3) );
(%o5) true
@end example
Note that @code{dispJordan(%o3)} is the Jordan form of matrix @code{a}.
To use this function write first @code{load("diag")}. See also @code{jordan} and @code{dispJordan}.
@opencatbox
@category{Package diag}
@closecatbox
@end deffn
@deffn {Function} mat_function (@var{f},@var{mat})
Returns @math{f(mat)}, where @var{f} is an analytic function and @var{mat}
a matrix. This computation is based on Cauchy's integral formula, which states that
if @code{f(x)} is analytic and
@example
mat = diag([JF(m1,n1),...,JF(mk,nk)]),
@end example
then
@example
f(mat) = ModeMatrix*diag([f(JF(m1,n1)), ..., f(JF(mk,nk))])
*ModeMatrix^^(-1)
@end example
Note that there are about 6 or 8 other methods for this calculation.
Some examples follow.
Example 1:
@example
(%i1) load("diag")$
(%i2) b2:matrix([0,1,0], [0,0,1], [-1,-3,-3])$
(%i3) mat_function(exp,t*b2);
2 - t
t %e - t - t
(%o3) matrix([-------- + t %e + %e ,
2
- t - t - t
2 %e %e - t - t %e
t (- ----- - ----- + %e ) + t (2 %e - -----)
t 2 t
t
- t - t - t
- t - t %e 2 %e %e
+ 2 %e , t (%e - -----) + t (----- - -----)
t 2 t
2 - t - t - t
- t t %e 2 %e %e - t
+ %e ], [- --------, - t (- ----- - ----- + %e ),
2 t 2
t
- t - t 2 - t
2 %e %e t %e - t
- t (----- - -----)], [-------- - t %e ,
2 t 2
- t - t - t
2 %e %e - t - t %e
t (- ----- - ----- + %e ) - t (2 %e - -----),
t 2 t
t
- t - t - t
2 %e %e - t %e
t (----- - -----) - t (%e - -----)])
2 t t
(%i4) ratsimp(%);
[ 2 - t ]
[ (t + 2 t + 2) %e ]
[ -------------------- ]
[ 2 ]
[ ]
[ 2 - t ]
(%o4) Col 1 = [ t %e ]
[ - -------- ]
[ 2 ]
[ ]
[ 2 - t ]
[ (t - 2 t) %e ]
[ ---------------- ]
[ 2 ]
[ 2 - t ]
[ (t + t) %e ]
[ ]
Col 2 = [ 2 - t ]
[ - (t - t - 1) %e ]
[ ]
[ 2 - t ]
[ (t - 3 t) %e ]
[ 2 - t ]
[ t %e ]
[ -------- ]
[ 2 ]
[ ]
[ 2 - t ]
Col 3 = [ (t - 2 t) %e ]
[ - ---------------- ]
[ 2 ]
[ ]
[ 2 - t ]
[ (t - 4 t + 2) %e ]
[ -------------------- ]
[ 2 ]
@end example
Example 2:
@example
(%i5) b1:matrix([0,0,1,1,1],
[0,0,0,1,1],
[0,0,0,0,1],
[0,0,0,0,0],
[0,0,0,0,0])$
(%i6) mat_function(exp,t*b1);
[ 2 ]
[ t ]
[ 1 0 t t -- + t ]
[ 2 ]
[ ]
(%o6) [ 0 1 0 t t ]
[ ]
[ 0 0 1 0 t ]
[ ]
[ 0 0 0 1 0 ]
[ ]
[ 0 0 0 0 1 ]
(%i7) minimalPoly(jordan(b1));
3
(%o7) x
(%i8) ident(5)+t*b1+1/2*(t^2)*b1^^2;
[ 2 ]
[ t ]
[ 1 0 t t -- + t ]
[ 2 ]
[ ]
(%o8) [ 0 1 0 t t ]
[ ]
[ 0 0 1 0 t ]
[ ]
[ 0 0 0 1 0 ]
[ ]
[ 0 0 0 0 1 ]
(%i9) mat_function(exp,%i*t*b1);
[ 2 ]
[ t ]
[ 1 0 %i t %i t %i t - -- ]
[ 2 ]
[ ]
(%o9) [ 0 1 0 %i t %i t ]
[ ]
[ 0 0 1 0 %i t ]
[ ]
[ 0 0 0 1 0 ]
[ ]
[ 0 0 0 0 1 ]
(%i10) mat_function(cos,t*b1)+%i*mat_function(sin,t*b1);
[ 2 ]
[ t ]
[ 1 0 %i t %i t %i t - -- ]
[ 2 ]
[ ]
(%o10) [ 0 1 0 %i t %i t ]
[ ]
[ 0 0 1 0 %i t ]
[ ]
[ 0 0 0 1 0 ]
[ ]
[ 0 0 0 0 1 ]
@end example
Example 3:
@example
(%i11) a1:matrix([2,1,0,0,0,0],
[-1,4,0,0,0,0],
[-1,1,2,1,0,0],
[-1,1,-1,4,0,0],
[-1,1,-1,1,3,0],
[-1,1,-1,1,1,2])$
(%i12) fpow(x):=block([k],declare(k,integer),x^k)$
(%i13) mat_function(fpow,a1);
[ k k - 1 ] [ k - 1 ]
[ 3 - k 3 ] [ k 3 ]
[ ] [ ]
[ k - 1 ] [ k k - 1 ]
[ - k 3 ] [ 3 + k 3 ]
[ ] [ ]
[ k - 1 ] [ k - 1 ]
[ - k 3 ] [ k 3 ]
(%o13) Col 1 = [ ] Col 2 = [ ]
[ k - 1 ] [ k - 1 ]
[ - k 3 ] [ k 3 ]
[ ] [ ]
[ k - 1 ] [ k - 1 ]
[ - k 3 ] [ k 3 ]
[ ] [ ]
[ k - 1 ] [ k - 1 ]
[ - k 3 ] [ k 3 ]
[ 0 ] [ 0 ]
[ ] [ ]
[ 0 ] [ 0 ]
[ ] [ ]
[ k k - 1 ] [ k - 1 ]
[ 3 - k 3 ] [ k 3 ]
[ ] [ ]
Col 3 = [ k - 1 ] Col 4 = [ k k - 1 ]
[ - k 3 ] [ 3 + k 3 ]
[ ] [ ]
[ k - 1 ] [ k - 1 ]
[ - k 3 ] [ k 3 ]
[ ] [ ]
[ k - 1 ] [ k - 1 ]
[ - k 3 ] [ k 3 ]
[ 0 ]
[ ] [ 0 ]
[ 0 ] [ ]
[ ] [ 0 ]
[ 0 ] [ ]
[ ] [ 0 ]
Col 5 = [ 0 ] Col 6 = [ ]
[ ] [ 0 ]
[ k ] [ ]
[ 3 ] [ 0 ]
[ ] [ ]
[ k k ] [ k ]
[ 3 - 2 ] [ 2 ]
@end example
To use this function write first @code{load("diag")}.
@opencatbox
@category{Package diag}
@closecatbox
@end deffn
|