[GiNaC-list] Differentiate matrix wrt vector

[Vladimir V. Kisil]

	Hello,

	I am not sure what do you mean by "differentiate a matrix wrt to
  a vector", is it a sort of gradient? In any case, if you could express your
  aim through the standard partial derivatives of functions (which
  GiNaC can do) you will succeed.

  Best wishes,
  Vladimir
-- 
Vladimir V. Kisil                 http://www.maths.leeds.ac.uk/~kisilv/
  Book:      Geometry of Mobius Maps       https://doi.org/10.1142/p835
  Soft:      Geometry of cycles         http://moebinv.sourceforge.net/
  Jupyter notebooks:       https://github.com/vvkisil/MoebInv-notebooks
>>>>> On Wed, 3 Mar 2021 14:42:30 +0200, Orxan Shibliyev <orxan.shibli at gmail.com> said:

    OSh> Suppose, I have a 5x5 matrix and I want to differentiate the
    OSh> matrix wrt to a 5x1 matrix in order to obtain a 3D matrix or
    OSh> tensor. In the following code, A.diff(uL); cannot compile. Is
    OSh> it possible to differentiate a matrix with symbolic elements
    OSh> wrt to a vector which also contains symbols?

    OSh> #include <iostream> #include <ginac/ginac.h> using namespace
    OSh> std; using namespace GiNaC;

    OSh> int main() { const int DIM = 5;

    OSh>     symbol g("g");

    OSh>     symbol uL1("uL1"); symbol uL2("uL2"); symbol uL3("uL3");
    OSh> symbol uL4("uL4"); symbol uL5("uL5");

    OSh>     matrix uL = { {uL1}, {uL2}, {uL3}, {uL4}, {uL5} };

    OSh>     auto qL = matrix(DIM, 1);

    OSh>     qL(0,0) = sqrt(uL1); qL(1,0) = uL2 / qL(0,0); qL(2,0) = uL3
    OSh> / qL(0,0); qL(3,0) = uL4 / qL(0,0); qL(4,0) = (uL5 + (g - 1) *
    OSh> (uL5 - 0.5 * (pow(uL2,2) + pow(uL3,2) + pow(uL4,2)) / uL1)) /
    OSh> uL1;

    OSh>     symbol uR1("uR1"); symbol uR2("uR2"); symbol uR3("uR3");
    OSh> symbol uR4("uR4"); symbol uR5("uR5");

    OSh>     matrix uR = { {uR1}, {uR2}, {uR3}, {uR4}, {uR5} };

    OSh>     auto qR = matrix(DIM, 1);

    OSh>     qR(0,0) = sqrt(uR1); qR(1,0) = uR2 / qR(0,0); qR(2,0) = uR3
    OSh> / qR(0,0); qR(3,0) = uR4 / qR(0,0); qR(4,0) = (uR5 + (g - 1) *
    OSh> (uR5 - 0.5 * (pow(uR2,2) + pow(uR3,2) + pow(uR4,2)) / uR1)) /
    OSh> uR1;

    OSh>     auto q = qL.add(qR); q.mul_scalar(0.5);

    OSh>     matrix B = { {2*q(0,0), 0, 0, 0, 0}, {q(1,0), q(0,0), 0, 0,
    OSh> 0}, {q(1,0), q(0,0), 0, 0, 0}, {q(2,0), 0, q(0,0), 0, 0},
    OSh> {q(3,0), 0, 0, q(0,0), 0}, {q(4,0)/g, (g-1)*q(1,0)/g,
    OSh> (g-1)*q(2,0)/g, (g-1)*q(3,0)/g, q(0,0)/g} };

    OSh>     matrix C = { {q(1,0), q(0,0), 0, 0, 0}, {(g-1)*q(4,0)/g,
    OSh> (g+1)*q(1,0)/g, (1-g)*q(2,0)/g, (1-g)*q(3,0)/g,
    OSh> (g-1)*q(0,0)/g}, {0, q(2,0), q(1,0), 0, 0}, {0, q(3,0), 0,
    OSh> q(1,0), 0}, {0, q(4,0), 0, 0, q(1,0)} };

    OSh>     auto A = B.mul(C.inverse());

    OSh>     A.diff(uL);

    OSh>     return 0; }

    OSh> ----------------------------------------------------
    OSh> Alternatives:

    OSh> ----------------------------------------------------
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