Constructs a square matrix with the matrices of lm in the diagonal. lm is a list of matrices or scalars.
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 ]
To use this function write first load("diag").
Returns the Jordan cell of order n with eigenvalue lambda.
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 ]
To use this function write first load("diag").
Returns the Jordan form of matrix mat, but codified in a Maxima list.
To get the corresponding matrix, call function dispJordan using as
argument the output of jordan.
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 ]
To use this function write first load("diag"). See also dispJordan
and minimalPoly.
Returns the Jordan matrix associated to the codification given by the Maxima
list l, which is the output given by function jordan.
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 ]
To use this function write first load("diag"). See also jordan
and minimalPoly.
Returns the minimal polynomial associated to the codification given by the
Maxima list l, which is the output given by function jordan.
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)
To use this function write first load("diag"). See also jordan
and dispJordan.
Returns the matrix M such that \((M^^-1).A.M=J\), where J is
the Jordan form of A. The Maxima list l is the codified form of
the Jordan form as returned by function jordan.
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
Note that dispJordan(%o3) is the Jordan form of matrix a.
To use this function write first load("diag"). See also jordan
and dispJordan.
Returns \(f(mat)\), where f is an analytic function and mat
a matrix. This computation is based on Cauchy’s integral formula, which states
that if f(x) is analytic and
mat = diag([JF(m1,n1), ..., JF(mk,nk)]), then f(mat) =
ModeMatrix * diag([f(JF(m1,n1)), ..., f(JF(mk,nk))]) * ModeMatrix^^(-1).
Note that there are about 6 or 8 other methods for this calculation.
Some examples follow.
To use this function write first load("diag").
Example 1:
(%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 ]
Example 2:
(%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 ]
Example 3:
(%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 ]