On Apr 6, 8:39 pm, John Cremona wrote:
> where A^* is the conjugate transpose.
You mean the "adjoint of a matrix", right? ;-)
I hijacked this topic and regenerated it over on sage-devel - should
have posted a link earlier:
http://groups.google.com/group/sage-devel/browse_thread/thread/86329
Indeed, this seems very reasonable. It might be better to implement it
separately, though, since computing A^*A might take much longer than just
squaring the elements and adding them, to get trace(A^*A).
-Keshav
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I agree. It makes no sense at all to me for A.abs() to return the
determinant of A.
For real or complex matrices it would make sense for A.abs() to be
sqrt(trace(A^*A)) where A^* is the conjugate transpose. This is just
the square root of the sums of the squares of the absolute values of
the ent
On Apr 4, 2011, at 15:19 , John H Palmieri wrote:
> On Monday, April 4, 2011 3:00:20 PM UTC-7, pong wrote:
>>
>> By that I simply mean a function that on input a real matrix M returns
>> the matrix N such that n[i][j] = abs(m[i][j]).
>>
>> This can be achieve by something like:
>>
>> n = le
On Monday, April 4, 2011 3:00:20 PM UTC-7, pong wrote:
>
> By that I simply mean a function that on input a real matrix M returns
> the matrix N such that n[i][j] = abs(m[i][j]).
>
> This can be achieve by something like:
>
> n = len(M.rows()); m =len(M.columns()); N = matrix(n,m,lambda i,j:
>
