Hi,
from what I've been reading, and testing myself, 64bit CPU's from AMD
and actually it seems like almost all 64bit other than IA64, use em64t
in MKL - but in Numpy (at least 1.4.1), this architecture is picked
only for Xeon - though older Xeons were not 64 bit iirc - I'm talking
about numpy/dis
On Sat, May 1, 2010 at 15:36, Gökhan Sever wrote:
> Hello,
>
> Is "b" an expected value? I am suspecting another floating point arithmetic
> issue.
>
> I[1]: a = np.arange(1.6, 1.8, 0.1, dtype='float32')
>
> I[2]: a
> O[2]: array([ 1.6002, 1.7005], dtype=float32)
>
> I[3]: b = np.arange(1
Gökhan Sever wrote:
> Hello,
>
> Is "b" an expected value? I am suspecting another floating point
> arithmetic issue.
Exactly. You'll see the same type of problem with float64, too:
In [17]: z = np.arange(1.7, 1.8, 0.1)
In [18]: z
Out[18]: array([ 1.7, 1.8])
In [19]: z[1] == 1.8
Out[19]: Tr
I ran into this issue and it was discussed on the pystatsmodels mailing
list.
Here is the setup
Running on a Mac 10.6
Using Office 2008
Saving an spreadsheet using excel "save as" a csv file.
Try to import using genfromtxt fails, report a EOL error
I thought this was because the EOL was wrong, It
On Sat, May 1, 2010 at 1:36 PM, Gökhan Sever wrote:
> Hello,
>
> Is "b" an expected value? I am suspecting another floating point arithmetic
> issue.
>
> I[1]: a = np.arange(1.6, 1.8, 0.1, dtype='float32')
>
> I[2]: a
> O[2]: array([ 1.6002, 1.7005], dtype=float32)
>
> I[3]: b = np.arange
On 1 May 2010 16:36, Gökhan Sever wrote:
> Hello,
>
> Is "b" an expected value? I am suspecting another floating point arithmetic
> issue.
>
> I[1]: a = np.arange(1.6, 1.8, 0.1, dtype='float32')
>
> I[2]: a
> O[2]: array([ 1.6002, 1.7005], dtype=float32)
>
> I[3]: b = np.arange(1.7, 1.8,
