On Mon, Dec 1, 2008 at 10:30 AM, Darren Dale <[EMAIL PROTECTED]> wrote:
>
>
> On Mon, Dec 1, 2008 at 3:12 AM, Gael Varoquaux <
> [EMAIL PROTECTED]> wrote:
>
>> On Mon, Dec 01, 2008 at 12:44:10PM +0900, David Cournapeau wrote:
>> > On Mon, Dec 1, 2008 at 7:00 AM, Darren Dale <[EMAIL PROTECTED]> wro
All,
Here's the latest version of genloadtxt, with some recent corrections.
With just a couple of tweaking, we end up with some decent speed: it's
still slower than np.loadtxt, but only 15% so according to the test at
the end of the package.
And so, now what ? Should I put the module in nu
> Another possibility would be to use HDF5 as a data container. It
> supports the fletcher32 filter [1] which basically computes a chuksum
> for evey data chunk written to disk and then always check that the data
> read satifies the checksum kept on-disk. So, if the HDF5 layer doesn't
> comp
A Friday 05 December 2008, Brennan Williams escrigué:
> Robert Kern wrote:
> > On Thu, Dec 4, 2008 at 18:54, Brennan Williams
> >
> > <[EMAIL PROTECTED]> wrote:
> >> Thanks
> >>
> >> [EMAIL PROTECTED] wrote:
> >>> I didn't check what this does behind the scenes, but try this
> >>
> >> import hashli
Hi all
I'm subclassing ndarray following [1] and I'd like to know if i'm doing
it right. My goals are
- ndarray subclass MyArray with additional methods
- replacement for np.array, np.asarray on module level returning MyArray
instances
- expose new methods as functions on module level
Pierre GM wrote:
> On Dec 4, 2008, at 7:22 AM, Manuel Metz wrote:
>> Will loadtxt in that case remain as is? Or will the _faulttolerantconv
>> class be used?
>
> No idea, we need to discuss it. There's a problem with
> _faulttolerantconv: using np.nan as default value will not work in
> Python
