On 7/14/07, Robert Kern [EMAIL PROTECTED] wrote:
Sebastian Haase wrote:
Hi.
Two things.
1) The doc-string of numpy.where() states that transpose(where(cond,
x,y)) whould always return a 2d-array. How can this be true?? It also
says (before) that if x,y are given where(cond,x,y) always
Hi,
I compared for a 256x256 float32 normal-noise (x0=100,sigma=1) array
the times to do
1./ (a*a)
vs.
a**-2
U.timeIt('1./(a*a)', 1000)
(0.00090877471871, 0.00939644563778, 0.00120674694689, 0.00068554628)
U.timeIt('a**-2', 1000)
(0.00876591857354, 0.0263829620803, 0.00952076311375,
Sebastian Haase wrote:
On 7/14/07, Robert Kern [EMAIL PROTECTED] wrote:
Sebastian Haase wrote:
2) Could we have another optional argument dtype in numpy.where()?
Otherwise I would have to always write code like this:
a = N.where( arrx, 1.0, 0.0)
a = a.astype(N.float32)
a = N.where(arr x,
On 7/15/07, Robert Kern [EMAIL PROTECTED] wrote:
Sebastian Haase wrote:
On 7/14/07, Robert Kern [EMAIL PROTECTED] wrote:
Sebastian Haase wrote:
2) Could we have another optional argument dtype in numpy.where()?
Otherwise I would have to always write code like this:
a = N.where( arrx,
On 7/15/07, Robert Kern [EMAIL PROTECTED] wrote:
Sebastian Haase wrote:
On 7/14/07, Robert Kern [EMAIL PROTECTED] wrote:
Sebastian Haase wrote:
2) Could we have another optional argument dtype in numpy.where()?
Otherwise I would have to always write code like this:
a = N.where( arrx,
On 7/15/07, Sebastian Haase [EMAIL PROTECTED] wrote:
Hi,
I compared for a 256x256 float32 normal-noise (x0=100,sigma=1) array
the times to do
1./ (a*a)
vs.
a**-2
U.timeIt('1./(a*a)', 1000)
(0.00090877471871, 0.00939644563778, 0.00120674694689, 0.00068554628)
U.timeIt('a**-2', 1000)
Greetings,
We're excited to have *Ivan Krstić*, the director of security
architecture for the One Laptop Per Child project as our Keynote
Speaker this year.
The planning for the SciPy 2007 Conference is moving along. Please
see below for some important updates.
Schedule Available
