On Fri, Jul 25, 2008 at 9:39 PM, Keith Goodman <[EMAIL PROTECTED]> wrote:
> On Fri, Jul 25, 2008 at 12:36 PM, Keith Goodman <[EMAIL PROTECTED]>
> wrote:
> > On Fri, Jul 25, 2008 at 12:32 PM, Frank Lagor <[EMAIL PROTECTED]>
> wrote:
> >> Perhaps I do not understand something properly, if so could s
On Fri, Jul 25, 2008 at 14:32, Frank Lagor <[EMAIL PROTECTED]> wrote:
> Perhaps I do not understand something properly, if so could someone please
> explain the behavior I notice with numpy.linalg.svd when acting on arrays.
> It gives the incorrect answer, but works fine with matrices. My numpy is
On Fri, Jul 25, 2008 at 12:36 PM, Keith Goodman <[EMAIL PROTECTED]> wrote:
> On Fri, Jul 25, 2008 at 12:32 PM, Frank Lagor <[EMAIL PROTECTED]> wrote:
>> Perhaps I do not understand something properly, if so could someone please
>> explain the behavior I notice with numpy.linalg.svd when acting on a
On Fri, Jul 25, 2008 at 12:32 PM, Frank Lagor <[EMAIL PROTECTED]> wrote:
> Perhaps I do not understand something properly, if so could someone please
> explain the behavior I notice with numpy.linalg.svd when acting on arrays.
> It gives the incorrect answer, but works fine with matrices. My numpy
Perhaps I do not understand something properly, if so could someone please
explain the behavior I notice with numpy.linalg.svd when acting on arrays.
It gives the incorrect answer, but works fine with matrices. My numpy is
1.1.0.
>>> R = n.array([[3.6,.35],[.35,1.8]])
>>> V,D,W = n.linalg.svd(R)
