Also Faisal just opened a pull request implementing this:

https://github.com/sympy/sympy/pull/19703

Does that look like what you expected? Feel free to comment on the
pull request if you have any suggestions.

Oscar

On Sat, 4 Jul 2020 at 14:24, Kasper Peeters <kasper.peet...@phi-sci.com> wrote:
>
>
>> Is there a way to compute the gradient and hessian matrices of a vector 
>> field like u = (x) i + (2yz) j + (3xy) k.
>
>
> I know you didn't ask for this, but just in case it is of any help, here's 
> how you do it in Cadabra (https://cadabra.science).
> Cadabra uses Sympy under the hood, so it's at least a partial Sympy answer.
>
> Set-up with:
>
>    {x,y,z}::Coordinate;
>    {i,j,k,l}::Indices(values={x,y,z});
>    \partial{#}::PartialDerivative;
>    rl:= { u_{x} = x, u_{y} = 2 y z, u_{z} = 3 x y };
>
> The gradient can then be computed using:
>
>    grad:= g_{i j} = \partial_{i}{ u_{j} };
>    evaluate(grad, rl, rhsonly=True);
>
> and the Hessian with:
>
>    H:= H_{i j k} = \partial_{i j}{ u_{k} };
>    evaluate(H, rl, rhsonly=True);
>
> Hope this helps.
>
> Kasper
>
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