Re: [Numpy-discussion] Installation info

On Fri, May 30, 2008 at 8:35 PM, Hanni Ali <[EMAIL PROTECTED]> wrote: > I would also like to see a 64bit build for windows as well if possible. > > Unfortunately, this is difficult: windows 64 is not commonly available (I don't have any access to it personally, for example), and mingw is not avail

Re: [Numpy-discussion] Is this a bug?

Robert Kern wrote: > On Wed, May 28, 2008 at 7:52 PM, Travis E. Oliphant > <[EMAIL PROTECTED]> wrote: > >> Anne Archibald wrote: >> >>> 2008/5/27 Robert Kern <[EMAIL PROTECTED]>: >>> >>> Can we make it so that dtype('c') is preserved instead of displaying '|S1'? It does not

[Numpy-discussion] Multi-Core Cache Usage Analyzer

An HPC friend altered me to a recent announcement of a new memory-optimization product. The article in HPCwire is here: and the company website is here: . Note sure of something like this would

Re: [Numpy-discussion] PyTables, array and recarray

A Friday 30 May 2008, Hanno Klemm escrigué: > Hi, > > I try to save the contents of a numpy recarray with PyTables into a > file. That works well, however, if I then try to retrieve the data, I > get back an array with matching dtypes rather than a recarray. > > What is the best way to get a recarr

Re: [Numpy-discussion] behavior of 'insert' for inserting multiple values

mark wrote: > I think this is a special case that was overlooked. > It works if there are multiple positions but only one value: > a = arange(5) insert(a,[3,3],4) > array([0, 1, 2, 4, 4, 3, 4]) > > But not when you give one position with mutiple values: > insert(a

Re: [Numpy-discussion] PyTables, array and recarray

On Friday 30 May 2008 11:17:18 Hanno Klemm wrote: Hanno, Try a view: > >>> f.close() > >>> f = t.openFile('test.h5', 'r') > >>> b = f.root.test[:].view(N.recarray) Views are often the most efficient way to change the type of an array. ___ Numpy-discussio

[Numpy-discussion] PyTables, array and recarray

Hi, I try to save the contents of a numpy recarray with PyTables into a file. That works well, however, if I then try to retrieve the data, I get back an array with matching dtypes rather than a recarray. What is the best way to get a recarray back, or if that's not possible what's the most effi

Re: [Numpy-discussion] behavior of 'insert' for inserting multiple values

I think this is a special case that was overlooked. It works if there are multiple positions but only one value: >>> a = arange(5) >>> insert(a,[3,3],4) array([0, 1, 2, 4, 4, 3, 4]) But not when you give one position with mutiple values: >>> insert(a,3,[7,7]) array([0, 1, 2, 7, 3, 4]) It would be

Re: [Numpy-discussion] Question for Travis

On Fri, May 30, 2008 at 1:19 AM, Travis E. Oliphant <[EMAIL PROTECTED]> wrote: > Charles R Harris wrote: > > Travis, > > > > What are the fundamental types for ndarrays? We have the c types, > > 'bBhHiIlLqQfdg', together with the boolean and complex types. Then we > > have types defined by length,

Re: [Numpy-discussion] Installation info

I would also like to see a 64bit build for windows as well if possible. Hanni 2008/5/30 Peter Creasey <[EMAIL PROTECTED]>: > 2008/5/30 Peter Creasey <[EMAIL PROTECTED]>: > > Is numpy v1.1 going to come out in egg format? > > > > Oops, I didn't mean to mail with an entire numpy digest in the body

Re: [Numpy-discussion] Installation info

2008/5/30 Peter Creasey <[EMAIL PROTECTED]>: > Is numpy v1.1 going to come out in egg format? > Oops, I didn't mean to mail with an entire numpy digest in the body. sorry, Peter ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://project

[Numpy-discussion] Installation info

Is numpy v1.1 going to come out in egg format? I ask because I only see the superpack installers on the sourceforge page, and we have users who we are delivering to via egg - requires. thanks, Peter 2008/5/23 <[EMAIL PROTECTED]>: > Send Numpy-discussion mailing list submissions to >n

Re: [Numpy-discussion] Question about indexing

Hi Raul, There are a some points that might help you with indexing: 1) a[obj] is (basically) equivalent to a.__getitem__(numpy.index_exp[obj]) 2) obj is always converted to a tuple if it isn't one already: * numpy.index_exp[0,1] == (0,1) * numpy.index_exp[(0,1)] == (0,1) * numpy.index_exp[

Re: [Numpy-discussion] Question for Travis

Charles R Harris wrote: > Travis, > > What are the fundamental types for ndarrays? We have the c types, > 'bBhHiIlLqQfdg', together with the boolean and complex types. Then we > have types defined by length, int8, uint8, etc. The long types change > length going from 32 to 64 bit machines, so th