On Sat, Aug 8, 2009 at 10:09 PM, David Warde-Farley wrote:
> On 9-Aug-09, at 12:36 AM, T J wrote:
>
> z = array([1,2,3,4])
> z[[1]]
>> array([1])
> z[(1,)]
>> 1
>>
> In the special case of scalar indices they're treated as if they are
> length-1 tuples. The behaviour you're seeing is th
On 9-Aug-09, at 12:36 AM, T J wrote:
z = array([1,2,3,4])
z[[1]]
> array([1])
z[(1,)]
> 1
>
> I'm just curious: What is the motivation for this differing behavior?
When you address, i.e. an element in 2D array with a[2,3] you are
actually indexing z with a tuple object (2,3). The
>>> z = array([1,2,3,4])
>>> z[[1]]
array([1])
>>> z[(1,)]
1
I'm just curious: What is the motivation for this differing behavior?
Is it a necessary consequence of, for example, the following:
>>> z[z<3]
array([1,2])
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N
On Sat, Aug 8, 2009 at 8:54 PM, Neil Martinsen-Burrell wrote:
>
> The ellipsis is a built-in python constant called Ellipsis. The colon
> is a slice object, again a python built-in, called with None as an
> argument. So, z[...,2,:] == z[Ellipsis,2,slice(None)].
>
Very helpful! Thank you. I did
On Fri, Aug 7, 2009 at 11:54 AM, T J wrote:
> The reduce function of ufunc of a vectorized function doesn't seem to
> respect the dtype.
>
def a(x,y): return x+y
b = vectorize(a)
c = array([1,2])
b(c, c) # use once to populate b.ufunc
d = b.ufunc.reduce(c)
c.dtype, ty
On 2009-08-08 22:46 , T J wrote:
> I have an array, and I need to index it like so:
>
> z[...,x,:]
>
> How can I write code which will index z, as above, when x is not known
> ahead of time. For that matter, the particular dimension I am querying
> is not known either. In case this is still c
I have an array, and I need to index it like so:
z[...,x,:]
How can I write code which will index z, as above, when x is not known
ahead of time. For that matter, the particular dimension I am querying
is not known either. In case this is still confusing, I am looking
for the NumPy way to do
There is something curious here. The second flush() fails. Can anyone
explain this?
Tom
--- code snippet
...
# create a memmap with dtype and shape that matches the data
fp = np.memmap(filename, dtype='float32', mode='w+', shape=(3,4))
print "Initial me
You are welcome to merge it but I fear it is not stable enough.
I'd like to spend more time with it first.
-Travis
--
(mobile phone of)
Travis Oliphant
Enthought, Inc.
1-512-536-1057
http://www.enthought.com
On Aug 7, 2009, at 9:23 PM, Charles R Harris
wrote:
> I ask again,
>
> Datetime is
On Sat, Aug 8, 2009 at 10:33 AM, Pierre GM wrote:
>
> On Aug 7, 2009, at 11:23 PM, Charles R Harris wrote:
>
> > I ask again,
> >
> > Datetime is getting really stale and hasn't been touched recently.
> > Do the datetime folks want it merged or not, because it's getting to
> > be a bit of work.
>
On Aug 7, 2009, at 11:23 PM, Charles R Harris wrote:
> I ask again,
>
> Datetime is getting really stale and hasn't been touched recently.
> Do the datetime folks want it merged or not, because it's getting to
> be a bit of work.
Chuck,
Please check directly w/ Travis O. (and Robert ?), the
On Sat, Aug 8, 2009 at 10:33 PM, wrote:
> David Cournapeau wrote:
>> On Sat, Aug 8, 2009 at 9:38 PM, wrote:
>>> Hi,
>>>
>>> I got 16 test failures after building r7300 from svn on debian/sid/i386.
>>> Seems all related to complex linear algebra modules.
>>
>> Are you using atlas ? (numpy.show_con
David Cournapeau wrote:
> On Sat, Aug 8, 2009 at 9:38 PM, wrote:
>> Hi,
>>
>> I got 16 test failures after building r7300 from svn on debian/sid/i386.
>> Seems all related to complex linear algebra modules.
>
> Are you using atlas ? (numpy.show_config() output)
Yes, it's libatlas-sse2 3.6.0-24 d
On Sat, Aug 8, 2009 at 9:38 PM, wrote:
> Hi,
>
> I got 16 test failures after building r7300 from svn on debian/sid/i386.
> Seems all related to complex linear algebra modules.
Are you using atlas ? (numpy.show_config() output)
If so, did you compile it by yourself ? Did you compile everything
w
Hi,
I got 16 test failures after building r7300 from svn on debian/sid/i386.
Seems all related to complex linear algebra modules.
Here's the error messages:
Running unit tests for numpy
NumPy version 1.4.0.dev7300
NumPy is installed in /var/opt/py/lib/python2.5/site-packages/numpy
Python version
On Fri, Aug 07, 2009 at 11:55:45PM -0400, josef.p...@gmail.com wrote:
> On Fri, Aug 7, 2009 at 10:17 PM, wrote:
> > Thanks! That helps a lot.
> Thanks for improving the docs.
Many thanks for taking the time of finding out what this distribution
really is, and improving the docs. I was also puzzl
Peter Jeremy wrote:
> [Apologies if anyone sees this twice - the first copy appears to have
> disappeared into a black hole]
>
> Should ATLAS be built with or without threading support for use with
> NumPy? The NumPy documentation just says that ATLAS will be used if
> found but gives no indicatio
[Apologies if anyone sees this twice - the first copy appears to have
disappeared into a black hole]
Should ATLAS be built with or without threading support for use with
NumPy? The NumPy documentation just says that ATLAS will be used if
found but gives no indication of how ATLAS should be built.
On 8-Aug-09, at 12:53 AM, Dr. Phillip M. Feldman wrote:
>
> I'd like to be able to make a slice of a 3-dimensional array, doing
> something
> like the following:
>
> Y= X[A, B, C]
>
> where A, B, and C are lists of indices. This works, but has an
> unexpected
> side-effect. When A, B, or C is
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