Re: [Numpy-discussion] Performance of defmatrix.py:103(__array_finalize__)

On 7/19/06, Travis Oliphant <[EMAIL PROTECTED]> wrote: Are you now using SVN NumPy, or are we still looking at NumPy 0.9.8 numbers?Sorry -- SVN updated as of about two hours ago.Thanks,-Kevin - Take Surveys. Earn Cash. Influenc

Re: [Numpy-discussion] Performance of defmatrix.py:103(__array_finalize__)

Kevin Jacobs <[EMAIL PROTECTED]> wrote: > On 7/19/06, *Travis Oliphant* <[EMAIL PROTECTED] > > wrote: > > Kevin Jacobs <[EMAIL PROTECTED] > > wrote: > > On 7/19/06, *Kevin Jacobs <[EMAIL PROTECTED] > >

Re: [Numpy-discussion] Performance of defmatrix.py:103(__array_finalize__)

Kevin Jacobs <[EMAIL PROTECTED]> wrote: > Hi all, > > Is it expected that the following script would spend over half of the > total execution time in defmatrix.py:103(__array_finalize__)? > > from numpy import matrix > > m=matrix( (1,1) ) > for i in range(100): > m[0,0] = 0. > > > Python ver

Re: [Numpy-discussion] Performance of defmatrix.py:103(__array_finalize__)

On 7/19/06, Kevin Jacobs <[EMAIL PROTECTED]> <[EMAIL PROTECTED]> wrote: Is it expected that the following script would spend over half of the total execution time in defmatrix.py:103(__array_finalize__)?Confirmed that a similar overhead exists for arrays, though not as extreme.  My application req

[Numpy-discussion] Performance of defmatrix.py:103(__array_finalize__)

Hi all,Is it expected that the following script would spend over half of the total execution time in defmatrix.py:103(__array_finalize__)?from numpy import matrixm=matrix( (1,1) )for i in range(100):   m[0,0] = 0.Python version is 2.5b1, NumPy 0.9.8.More importantly, is there a way to avoid thi