Suppose, I have a 5x5 matrix and I want to differentiate the matrix wrt to a 5x1 matrix in order to obtain a 3D matrix or tensor. In the following code, A.diff(uL); cannot compile. Is it possible to differentiate a matrix with symbolic elements wrt to a vector which also contains symbols? #include <iostream> #include <ginac/ginac.h> using namespace std; using namespace GiNaC; int main() { const int DIM = 5; symbol g("g"); symbol uL1("uL1"); symbol uL2("uL2"); symbol uL3("uL3"); symbol uL4("uL4"); symbol uL5("uL5"); matrix uL = { {uL1}, {uL2}, {uL3}, {uL4}, {uL5} }; auto qL = matrix(DIM, 1); qL(0,0) = sqrt(uL1); qL(1,0) = uL2 / qL(0,0); qL(2,0) = uL3 / qL(0,0); qL(3,0) = uL4 / qL(0,0); qL(4,0) = (uL5 + (g - 1) * (uL5 - 0.5 * (pow(uL2,2) + pow(uL3,2) + pow(uL4,2)) / uL1)) / uL1; symbol uR1("uR1"); symbol uR2("uR2"); symbol uR3("uR3"); symbol uR4("uR4"); symbol uR5("uR5"); matrix uR = { {uR1}, {uR2}, {uR3}, {uR4}, {uR5} }; auto qR = matrix(DIM, 1); qR(0,0) = sqrt(uR1); qR(1,0) = uR2 / qR(0,0); qR(2,0) = uR3 / qR(0,0); qR(3,0) = uR4 / qR(0,0); qR(4,0) = (uR5 + (g - 1) * (uR5 - 0.5 * (pow(uR2,2) + pow(uR3,2) + pow(uR4,2)) / uR1)) / uR1; auto q = qL.add(qR); q.mul_scalar(0.5); matrix B = { {2*q(0,0), 0, 0, 0, 0}, {q(1,0), q(0,0), 0, 0, 0}, {q(1,0), q(0,0), 0, 0, 0}, {q(2,0), 0, q(0,0), 0, 0}, {q(3,0), 0, 0, q(0,0), 0}, {q(4,0)/g, (g-1)*q(1,0)/g, (g-1)*q(2,0)/g, (g-1)*q(3,0)/g, q(0,0)/g} }; matrix C = { {q(1,0), q(0,0), 0, 0, 0}, {(g-1)*q(4,0)/g, (g+1)*q(1,0)/g, (1-g)*q(2,0)/g, (1-g)*q(3,0)/g, (g-1)*q(0,0)/g}, {0, q(2,0), q(1,0), 0, 0}, {0, q(3,0), 0, q(1,0), 0}, {0, q(4,0), 0, 0, q(1,0)} }; auto A = B.mul(C.inverse()); A.diff(uL); return 0; }