On Wed, Feb 2, 2011 at 4:46 PM, Robert Kern wrote:
> On Wed, Feb 2, 2011 at 21:42, Ilya Shlyakhter wrote:
>> Does numpy have a relational join operation for joining recordarrays?
>
> [~]
> |1> from numpy.lib import recfunctions
>
> [~]
> |2> recfunctions.join_by?
> Type: function
> Base
On Wed, Feb 2, 2011 at 21:42, Ilya Shlyakhter wrote:
> Does numpy have a relational join operation for joining recordarrays?
[~]
|1> from numpy.lib import recfunctions
[~]
|2> recfunctions.join_by?
Type: function
Base Class:
String Form:
Namespace: Interactive
File:
/Libr
Does numpy have a relational join operation for joining recordarrays?
thanks,
ilya
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Just wanted to make the developers aware of this bug that causes one of
our pyfits unit tests to fail:
http://projects.scipy.org/numpy/ticket/1733
Mike
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> It seems that using 64 bit python is the solution.
It's certainly the easy way to access a lot of memory -- and memory is
cheap these days.
> But the thing is i would
> compile my code and wanna distribute it to the clients..
I don't think 64 bit gets in the way of that -- except that it will
On Wed, Jan 12, 2011 at 1:05 PM, Pauli Virtanen wrote:
> Wed, 12 Jan 2011 17:34:32 +, Grégory Guyomarc'h wrote:
> [clip]
>> y = (numpy.dot(m, x) - 13.90901663) * 1000.0 print y[0]
> [clip]
>> Also, I could not reproduce it with older versions of numpy such as 1.3.
>> Is this behavior exp
On Wed, Feb 2, 2011 at 8:22 AM, Asmi Shah wrote:
> Hi all,
> It seems that using 64 bit python is the solution. But the thing is i would
> compile my code and wanna distribute it to the clients.. and that is the
> only reason why i want to work on 32 bit system. Sturla, how I can make it
> sure th
Hi all,
It seems that using 64 bit python is the solution. But the thing is i would
compile my code and wanna distribute it to the clients.. and that is the
only reason why i want to work on 32 bit system. Sturla, how I can make it
sure that some part of the data is kept on the disk and only the n
