On 04/23/2013 12:32 AM, Aaron Meurer wrote:
Is this the same thing as the matrix derivative described in the
matrix cookbook (see
https://code.google.com/p/sympy/issues/detail?id=2759)? If so, then
the answer is no.
Aaron Meurer
On Sun, Apr 21, 2013 at 7:28 AM, Saurabh Jha <saurabh.j...@gmail.com> wrote:
Hi,
I wanted to know if something like this is already implemented in
sympy?
for a function f: R(m × n)--> R mapping from mapping from m × n
matrices(let's say A) to real numbers than,
∇Af(A) =[∂f/∂A(11).............∂f/∂A(1n) ]
[ ]
[ ]
[∂f/∂A(n1)..............∂f/∂A(nn)]
Note: with ∇Af(A), I meant taking gradient of f(A) with respect to
matrix A and with ∂f/∂A(11), I meant taking derivative of function f
with respect to element A(11) of matrix A.
-Saurabh Jha
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Are you talking about the directional derivative of a matrix where if A
is a matrix and f(A) is a function of the matrix then
B\cdot\partial_{A}f = \lim_{h \rightarrow 0} f(A+hB)
so if A is a m x n matrix you simply regard the matrix as a vector of
length m x n. The dot product is defined for
m x n vectors.
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