On 10/12/07, adrianmatematico <[EMAIL PROTECTED]> wrote:
>
> Maybe I have something wrong with my installation.
> But Thanks a lot
>
> This is what sage told me (I erased the email addresses):
>
> sage: hg_sage.patch('/home/soto/Desktop/856.patch')
You have to do
hg_sage.import_patch('/home/
Maybe I have something wrong with my installation.
But Thanks a lot
This is what sage told me (I erased the email addresses):
sage: hg_sage.patch('/home/soto/Desktop/856.patch')
WARNING:
Make sure to create a ~/.hgrc file:
--
[
THANKS!!!
-Adrian.
On Oct 11, 11:08 pm, "Mike Hansen" <[EMAIL PROTECTED]> wrote:
> Hello,
>
> I've attached a patch that fixes the issues that you've mentioned. To
> apply it, run hg_sage.patch('/path/to/856.patch') from SAGE, exit
> SAGE, and then run ./sage -br .
>
> There still is some wo
Hello,
I've attached a patch that fixes the issues that you've mentioned. To
apply it, run hg_sage.patch('/path/to/856.patch') from SAGE, exit
SAGE, and then run ./sage -br .
There still is some work to be done with numpy support -- for example,
getting the numpy integer types to play well with
First of all: Sorry, I duplicated the bug...
Things change when instead of a 'f' I write float:
sage: a=numpy.array([[1,2,3],[4,5,6],[7,8,9]],float)
sage: a
array([[ 1., 2., 3.],
[ 4., 5., 6.],
[ 7., 8., 9.]])
sage: matrix(a)
[1.0 2.0 3.0]
[4.0 5.0 6.0]
[7.0 8.0 9.0]
sage
Hello,
Are you running a 64-bit machine?
I looked at the code, and the problem seems to come from the fact that
it is doing a naive check on the type of the numpy array; it is
currently assuming that your float32 array is a float64 array which is
why you are getting the strange results you are.
