Re: [Numpy-discussion] Is this a bug in numpy.ma.reduce?

2010-03-07 Thread David Goldsmith
On Sun, Mar 7, 2010 at 4:41 AM, Friedrich Romstedt < friedrichromst...@gmail.com> wrote: > 2010/3/5 Pierre GM : > > 'm'fraid no. I gonna have to investigate that. Please open a ticket with > a self-contained example that reproduces the issue. > > Thx in advance... > > P. > > I would like to stress

Re: [Numpy-discussion] Why is the shape of a singleton array the empty tuple?

2010-03-07 Thread David Goldsmith
On Sun, Mar 7, 2010 at 4:30 AM, Friedrich Romstedt < friedrichromst...@gmail.com> wrote: > First, to David's routine: > > 2010/3/7 David Goldsmith : > > def convert_close(arg): > > arg = N.array(arg) > > if not arg.shape: > > arg = N.array((arg,)) > > if arg.size: > > t

Re: [Numpy-discussion] multiprocessing shared arrays and numpy

2010-03-07 Thread Gael Varoquaux
On Sun, Mar 07, 2010 at 07:00:03PM +, René Dudfield wrote: > 1. Mmap'd files are useful since you can reuse disk cache as program > memory. So large files don't waste ram on the disk cache. I second that. mmaping has worked very well for me for large datasets, especialy in the context of re

Re: [Numpy-discussion] multiprocessing shared arrays and numpy

2010-03-07 Thread René Dudfield
On Fri, Mar 5, 2010 at 7:29 PM, Brian Granger wrote: > Francesc, > >> Yeah, 10% of improvement by using multi-cores is an expected figure for >> memory >> bound problems.  This is something people must know: if their computations >> are >> memory bound (and this is much more common that one may in

Re: [Numpy-discussion] Is this a bug in numpy.ma.reduce?

2010-03-07 Thread Friedrich Romstedt
2010/3/5 Pierre GM : > 'm'fraid no. I gonna have to investigate that. Please open a ticket with a > self-contained example that reproduces the issue. > Thx in advance... > P. I would like to stress the fact that imo this is maybe not ticket and not a bug. The issue arises when calling a.max() or

Re: [Numpy-discussion] Why is the shape of a singleton array the empty tuple?

2010-03-07 Thread Friedrich Romstedt
First, to David's routine: 2010/3/7 David Goldsmith : > def convert_close(arg): > arg = N.array(arg) > if not arg.shape: > arg = N.array((arg,)) > if arg.size: > t = N.array([0 if N.allclose(temp, 0) else temp for temp in arg]) > if len(t.shape) - 1: >