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 -- You received this message because you are subscribed to the Google Groups "sympy" group. To post to this group, send email to sympy@googlegroups.com. To unsubscribe from this group, send email to sympy+unsubscr...@googlegroups.com. For more options, visit this group at http://groups.google.com/group/sympy?hl=en.