numpy/lib/test_io.pyonly uses StringIO in the test, no actual csv file
If I give the filename than I get a TypeError: Can't convert 'bytes'
object to str implicitly
from the statsmodels mailing list example
data = recfromtxt(open('./star98.csv', "U"), delimiter=",", skip_header=1,
>>
On Mon, Mar 28, 2011 at 3:34 PM, wrote:
> What is the recommended way to perform a stable sort on a recarray /
> structured array ?
>
> In the following example, I want to sort on name, while retaining the
> existing order in the case of equal values:
> values = [('a', 1), ('a', 0), ('b', 2)]
> d
On Mon, Mar 28, 2011 at 10:44 PM, Sturla Molden wrote:
> Den 28.03.2011 19:12, skrev Pearu Peterson:
> >
> > FYI, f2py in numpy 1.6.x supports also assumed shape arrays.
>
> How did you do that? Chasm-interop, C bindings from F03, or marshalling
> through explicit-shape?
>
The latter.
Basically
On Mon, Mar 28, 2011 at 10:45 AM, Eli Stevens (Gmail)
wrote:
> On Fri, Mar 25, 2011 at 11:14 AM, Eli Stevens (Gmail)
> wrote:
> > On Fri, Mar 25, 2011 at 10:35 AM, Mark Wiebe wrote:
> >> That said, I think starting a discussion with the Python core developers
> >> about the float16 type is worth
Den 28.03.2011 19:12, skrev Pearu Peterson:
>
> FYI, f2py in numpy 1.6.x supports also assumed shape arrays.
How did you do that? Chasm-interop, C bindings from F03, or marshalling
through explicit-shape?
Can f2py pass strided memory from NumPy to Fortran?
Sturla
___
What is the recommended way to perform a stable sort on a recarray /
structured array ?
In the following example, I want to sort on name, while retaining the
existing order in the case of equal values:
values = [('a', 1), ('a', 0), ('b', 2)]
dtype = [('name', 'S10'), ('val', 'i4')]
a = np.a
On Fri, Mar 25, 2011 at 11:14 AM, Eli Stevens (Gmail)
wrote:
> On Fri, Mar 25, 2011 at 10:35 AM, Mark Wiebe wrote:
>> That said, I think starting a discussion with the Python core developers
>> about the float16 type is worthwhile. There might be interest in supporting
>> the float16 type in the
On Mon, Mar 28, 2011 at 6:01 PM, Sturla Molden wrote
>
>
> I'll try to clarify this:
>
> ** Most Fortran 77 compilers (and beyond) assume explicit-shape and
> assumed-size arrays are contiguous blocks of memory. That is, arrays
> declared like a(m,n) or a(m,*). They are usually passed as a pointer
Dear Paul Anton,
thanks a lot for your suggestion. I was also successful with
[blas]
libraries = blas
library_dirs = $PREFIX/gotoblas2/lib
[lapack]
libraries = lapack
library_dirs = $PREFIX/gotoblas2/lib
but I had compile clapack as a shared library and place a symbolic link
ln -s $PREFIX/gotobl
Den 28.03.2011 14:28, skrev Dag Sverre Seljebotn:
>
> Sure, I realize that it is not standard. I'm mostly wondering whether
> major Fortran compilers support working with strided memory in practice
> (defined as you won't get out-of-memory-errors when passing around huge
> strided array subset).
O
Den 28.03.2011 17:01, skrev Sturla Molden:
>
> ** Most Fortran compilers will make a temporary copy when passing a
> non-contiguous array section to a subroutine expecting an explicit-shape
> or assumed-shape array.
Sorry, typo. The latter should be "assumed-size array".
Sturla
_
Den 28.03.2011 14:28, skrev Dag Sverre Seljebotn:
>
> Sure, I realize that it is not standard. I'm mostly wondering whether
> major Fortran compilers support working with strided memory in practice
> (defined as you won't get out-of-memory-errors when passing around huge
> strided array subset).
I
On 03/28/2011 12:55 PM, Sturla Molden wrote:
> Den 28.03.2011 09:34, skrev Dag Sverre Seljebotn:
>> What would we do exactly -- pass the entire underlying buffer to Fortran
>> and then re-slice it Fortran side?
> Pass a C pointer to the first element along with shape and strides, get
> a Fortran po
Den 28.03.2011 09:34, skrev Dag Sverre Seljebotn:
> What would we do exactly -- pass the entire underlying buffer to Fortran
> and then re-slice it Fortran side?
Pass a C pointer to the first element along with shape and strides, get
a Fortran pointer using c_f_pointer, then reslice the Fortran p
On 03/27/2011 08:54 PM, Sturla Molden wrote:
> Den 26.03.2011 19:31, skrev Christopher Barker:
>
>> To understand all this, you'll need to study up a bit on how numpy
>> arrays lay out and access the memory that they use: they use a concept
>> of "strided" memory. It's very powerful and flexible, b
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