Hello Amit,
The line of code you have given is not clear. Could you give a more
concrete example of a functionality that you're expecting ?
If you want to calculate the hessian of a function, Sympy has a
hessian function which takes in a function and a list of variables of
the function, and returns the hessian matrix of size m * m, where m is
number of variables.
In [4]: f = x**2*y
In [5]: f
Out[5]:
2
x ⋅y
In [6]: syms = [x,y]
In [7]: hessian(f, syms)
Out[7]:
⎡2⋅y 2⋅x⎤
⎢ ⎥
⎣2⋅x 0 ⎦
As to about other matrix calculus functions, it would help if you
could show what exactly do you want along with the corresponding
output you expect.
-Sherjil Ozair
On Jun 30, 7:10 am, Amit <amiti...@gmail.com> wrote:
> Hi,
>
> I am studying machine learning and lately I had to do some matrix
> calculus. I am using the 'The Matrix cookbook' to calculate things
> like the gradient and hessian of expressions like:
>
> {Z \alpha}^T (Z^T diag(\alpha) Z - ...)^{-1} Z \alpha
>
> where Z is a matrix and alpha a vector. This can get pretty ugly and
> tedious when done by hand.
> I looked for some automatic way to do this i.e. a CAS, but didn't find
> any (I am looking for something that can do this symbolically and not
> numerically).
> I was wandering why is it so. Is it too complicated? or maybe its not
> well defined?
>
> Thanks,
> Amit
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