k you in
> advance for your help.
>
>
>
> --
> View this message in context: http://numpy-discussion.10968.
> n7.nabble.com/How-to-use-user-input-as-equation-directly-tp43665.html
> Sent from the Numpy-discussion mailing list archive at Nabble.com.
> ____
Thank you Juan, I've just joined GitHub and I've submitted the description
of the bug.
On Tue, Jul 19, 2016 at 2:55 PM, Juan Nunez-Iglesias
wrote:
> https://github.com/numpy/numpy/issues
>
>
> From: John Ladasky
> Reply: Discussion of Numerical Python
>
> D
Hi Robert,
Thanks for your reply. If no one disagrees with you or with me that this
is a Numpy bug, I would appreciate being directed to the appropriate page
to submit a bug-fix request.
On Tue, Jul 19, 2016 at 2:43 PM, Robert Kern wrote:
> On Tue, Jul 19, 2016 at 10:41 PM, John Lada
rint
a numpy array is remote from the problem, and thus rather uninformative,
which is why I did not immediately diagnose my error.
Should this be considered a Numpy bug, or is there some reason that
set_printoptions would legitimately need to accept a dictionary
First, off sorry for the long turnaround on responding to these
questions. Below I have tried to respond to everyone's questions and
comments. I have restructured the order of the messages so that my
responses are a little more structured. If anybody has more thoughts
or questions, please let me kn
Takes an array and tacks on arbitrary dimensions on either side, which is
returned as a view always. Here are the relevant features:
* Creates a view of the array that has the dimensions before and after tacked
on to it.
* Takes the before and after arguments independent of each other and the
c
Hey Eric,
That's a good point. I remember seeing this behavior before and thought it was
a bit odd.
Best,
John
> On Mar 16, 2015, at 2:20 AM, numpy-discussion-requ...@scipy.org wrote:
>
> Send NumPy-Discussion mailing list submissions to
>numpy-discussion@scipy.org
>
The sample case of the issue ( https://github.com/numpy/numpy/issues/5558 ) is
shown below. A proposal to address this behavior can be found here (
https://github.com/numpy/numpy/pull/5580 ). Please give me your feedback.
I tried to change the mask of `a` through a subindexed view, but was unab
uld rather have a breaking change in the ma
module than in core.
Best,
John
>> > I think the question is if scalars should be acceptable for the first
>> > argument, not if it should be for the 2nd and 3rd argument.
>> >
>> > If scalar can be given for
on, maybe you will find the
implementation instructive. The functions I described take only a few
lines.
John Zwinck
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ly unusual), why force them to always type in the
boilerplate independent=True to make it work?
John Zwinck
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"independent" has no relevance when the array is
1-d, it can simply be ignored.
John Zwinck
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On 3 Oct 2014 07:09, "T J" wrote:
>
> Any bites on this?
>
> On Wed, Sep 24, 2014 at 12:23 PM, T J wrote:
>> Python's round function goes away from zero, so I am looking for the
NumPy equivalent (and using vectorize() seems undesirable). In this sense,
it seems that having a ufunc for this type o
On Thu, Oct 2, 2014 at 6:27 PM, Sebastian Wagner wrote:
> So, for non-structured arrays, the consens is an Exception. The question
> is, which one.
> AttributeError would be fully backwards compatible. Existing code checks
> for the method and if it exists, the object has fields.
> ValueError woul
On 1 Oct 2014 04:30, "Stephan Hoyer" wrote:
>
> On Tue, Sep 30, 2014 at 1:22 PM, Eelco Hoogendoorn <
hoogendoorn.ee...@gmail.com> wrote:
>>
>> On more careful reading of your words, I think we agree; indeed, if
keys() is present is should return an iterable; but I don't think it should
be present
this is exactly what I'm aiming at.
Thoughts?
John Zwinck
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I am in the process of trying to build numpy with OpenMP support but
have had several issues.
Has anyone else built it with success that could offer some guidance
in what needs to be passed at build time.
For reference I am using Atlas 3.10.2 built with OpenMP as well (-F
alg -fopenmp)
Thanks,
J
When I apply numpy.vectorize() to a function, documentation tools behave
inconsistently with regard to the new, vectorized function. The
function's __doc__ attribute does contain the docstring of the original
function as expected, but the built-in help() command displays the
documentation of th
When I apply numpy.vectorize() to a function, documentation tools behave
inconsistently with regard to the new, vectorized function. The function's
__doc__ attribute does contain the docstring of the original function as
expected, but the built-in help() command displays the documentation of the
On 08/22/2014 11:14 PM, Cleo Drakos wrote:
>
> How can I convert this numpy array so that its first element belongs
> to (49.875N,179.625W), i.e., upper left latitude and longitude
> respectively; and the last element belong to (49.625S,179.875E), i.e.,
> lower right latitute and longitude respe
Shawn (Yuxiang) -
The right way to compute this is using Runga-Kutta approximations. I'm not
aware if numpy supports these. -jm
__
John Mark Agosta
650 465-4707
johnmark.ago...@gmail.com *"Unpredictable consequences are the most
expected thin
I have the following C code which is an extension to my python code.
The python and C code use
#include
what is the equivalent I can use in numpy that causes the minimum code change?
I did look through the old messages but didn't really find the answer-any help
to a novice just starting out i
www.picloud.com
[2]
http://docs.picloud.com/**environment.html<http://docs.picloud.com/environment.html>
[3] http://docs.picloud.com/howto/pyscientifictools.html
[4] http://docs.picloud.com/howto/primer.html
Best Regards,
John
--
John Riley
PiCloud, Inc.
_
Here's a good article on the vagaries of python paths when installing a new
python. Thus you can check exactly how python finds its modules, to assure the
new install is working properly:
https://www.usenix.org/publications/login/august-2012-volume-37-number-4/import
John Mark Agosta
((5,5))
> x[[0,2,4]]+=numpy.random.rand(3,5)
> print x
>
> This won't work if in the list [0,2,4], there is index duplication,
> but with your new code, it will. I think it is the most used case of
> advanced indexing. At least, for our lab:)
>
> Fred
>
> On Mon, Jul 2,
Hi Fred,
That's an excellent idea, but I am not too familiar with this use case.
What do you mean by list in 'matrix[list]'? Is the use case, just
incrementing in place a sub matrix of a numpy matrix?
John
On Fri, Jun 29, 2012 at 11:43 AM, Frédéric Bastien wrote:
> Hi,
>
On Fri, Jun 29, 2012 at 2:20 PM, Jim Vickroy wrote:
> As a lurker and user, I too wish for a distinct numpy-users list. -- jv
>
>
This thread is a perfect example of why another list is needed. It's
currently 42 semi-philosophical posts about what kind community numpy
should be and what kinds o
On Thu, Jun 28, 2012 at 7:25 AM, Travis Oliphant wrote:
> Hey all,
>
> I'd like to propose dropping support for Python 2.4 in NumPy 1.8 (not the 1.7
> release). What does everyone think of that?
As a tangential point, MPL is dropping support for python2.4 in it's
next major release. As su
larifying.
>
> -Travis
>
> >
> > Fred
> >
> > On Tue, Jun 26, 2012 at 1:27 PM, John Salvatier
> > wrote:
> >> Can you clarify why it would be super hard? I just reused the code for
> >> advanced indexing (a modification of PyArray_SetMap). Am
Thanks nathaniel, that does tricky...
On Wed, Jun 27, 2012 at 9:25 AM, Nathaniel Smith wrote:
> On Tue, Jun 26, 2012 at 10:53 PM, John Salvatier
> wrote:
> > I want to support multiple types in the index_increment function that
> I've
> > written here:
> >
>
> Some examples would be nice. A lot of people did move already. And I haven't
> seen reports of those that tried and got stuck. Also, Debian and Python(x,
> y) have 1.6.2, EPD has 1.6.1.
In my company, the numpy for our production python install is well
behind 1.6. In the world of trading, the u
and do the addition operation for that
type. It looks like some of the numpy code uses .c.src files to do
templating. Is that what I want to do here? Is the syntax described
somewhere?
John
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On Tue, Jun 26, 2012 at 3:27 PM, Thouis (Ray) Jones wrote:
> +1 !
>
> Speaking as someone trying to get started in contributing to numpy, I
> find this discussion extremely off-putting. It's childish,
> meaningless, and spiteful, and I think it's doing more harm than any
> possible good that coul
ted as you said.
>
> Fred
>
> On Tue, Jun 26, 2012 at 1:27 PM, John Salvatier
> wrote:
> > Can you clarify why it would be super hard? I just reused the code for
> > advanced indexing (a modification of PyArray_SetMap). Am I missing
> something
> > crucial?
> >
>
Can you clarify why it would be super hard? I just reused the code for
advanced indexing (a modification of PyArray_SetMap). Am I missing
something crucial?
On Tue, Jun 26, 2012 at 9:57 AM, Travis Oliphant wrote:
>
> On Jun 26, 2012, at 11:46 AM, John Salvatier wrote:
>
> Hello
6.7.]
[ 8.9. 40. 11.]]
"""
Cheers,
John
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easy way to gain access to these
functions? Should I give up on this approach?
(The function I was trying to build is index_inc in here (
https://github.com/jsalvatier/advinc/blob/master/advinc/advinc.c))
Cheers,
John
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That does seem like it should work well if len(unique(idx)) is close to
len(x). Thanks!
On Wed, Jun 6, 2012 at 9:35 AM, Robert Kern wrote:
> On Wed, Jun 6, 2012 at 4:52 PM, Robert Cimrman
> wrote:
>
> > Yes (in that thread), but it applies also adding/assembling vectors into
> a
> > global vect
py.put.html
>
> On Wed, Jun 6, 2012 at 4:48 AM, John Salvatier
> wrote:
> > Hello,
> >
> > I've noticed that If you try to increment elements of an array with
> advanced
> > indexing, repeated indexes don't get repeatedly incremented. For example:
>
Hello,
I've noticed that If you try to increment elements of an array with
advanced indexing, repeated indexes don't get repeatedly incremented. For
example:
In [30]: x = zeros(5)
In [31]: idx = array([1,1,1,3,4])
In [32]: x[idx] += [2,4,8,10,30]
In [33]: x
Out[33]: array([ 0., 8., 0., 1
On 2012-05-11, at 4:01 PM, Norman Shelley wrote:
> Running on Linux RHEL4
>
> numpy.random.multivariate_normal seems to work well for 25 mean
> values but when I go to 26 mean values (and their corresponding
> covariance values) it produces garbage.
> Any ideas?
The implementation of multiv
really like to
know why and your answer alludes to that.
Please excuse my ignorance on this topic. Can you perhaps educate me a
little on 'literal kind values'? I take you to mean that
'int8' is not a literal kind value while 1 and 8 are examples of literal
kind values.
Thanks,
Thanks Sameer. I confirmed on my side as well. I will try to understand
the why part now. Much appreciated.
On Mon, Apr 16, 2012 at 11:58 PM, Sameer Grover
wrote:
> On Tuesday 17 April 2012 11:02 AM, John Mitchell wrote:
>
> Hi,
>
> I am using f2py to pass a numpy array of typ
on
bits = 100000001 0
Any Ideas?
thanks,
John
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On Mon, Mar 5, 2012 at 1:29 PM, Keith Goodman wrote:
>
> I[8] np.allclose(a, a[0])
> O[8] False
> I[9] a = np.ones(10)
> I[10] np.allclose(a, a[0])
> O[10] True
>
>
One disadvantage of using a[0] as a proxy is that the result depends on the
ordering of a
(a.max() - a.min()) < epsilon
is a
On Wed, Feb 29, 2012 at 1:20 PM, Neal Becker wrote:
>
> Much of Linus's complaints have to do with the use of c++ in the _kernel_.
> These objections are quite different for an _application_. For example,
> there
> are issues with the need for support libraries for exception handling.
> Not an
On Sat, Feb 18, 2012 at 5:09 PM, David Cournapeau wrote:
>
> There are better languages than C++ that has most of the technical
> benefits stated in this discussion (rust and D being the most
> "obvious" ones), but whose usage is unrealistic today for various
> reasons: knowledge, availability on
Hi
The plain gcc (non-llvm) is no longer there, if you install Lion and directly
Xcode 4.3.
Only, if you have the old Xcode 4.2 or lower, then you may have a non-llvm gcc.
For Xcode 4.3, I recommend installing the "Command Line Tools for Xcode" from
the preferences of Xcode. Then you'll have th
On 17.02.2012, at 21:46, Ralf Gommers wrote:
> [...]
> So far no one has managed to build the numpy/scipy combo with the LLVM-based
> compilers, so if you were willing to have a go at fixing that it would be
> hugely appreciated. See http://projects.scipy.org/scipy/ticket/1500 for
> details.
>
On Thu, Feb 16, 2012 at 7:26 PM, Alan G Isaac wrote:
> On 2/16/2012 7:22 PM, Matthew Brett wrote:
> > This has not been an encouraging episode in striving for consensus.
>
> I disagree.
> Failure to reach consensus does not imply lack of striving.
>
>
Hey Alan, thanks for your thoughtful and nuan
Wow, I wasn't aware of that even if I work with numpy for years now.
NumPy is amazing.
Samuel
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Thanks Mark!
John
On Wed, Feb 8, 2012 at 6:48 PM, Mark Wiebe wrote:
> Converting between date and datetime requires caution, because it depends
> on your time zone. Because all datetime64's are internally stored in UTC,
> simply casting as in your example treats it in UT
Hello, is there a good way to get just the date part of a datetime64?
Frequently datetime datatypes have month(), date(), hour(), etc functions
that pull out part of the datetime, but I didn't see those mentioned in the
datetime64 docs. Casting to a 'D' dtype didn't work as I would have hoped:
In
That makes sense.
I figured that ambiguity was the reason it was removed.
Thank you for the explanation. I'm a big fan of your work.
John
On Mon, Feb 6, 2012 at 1:18 PM, Mark Wiebe wrote:
> Hey John,
>
> NumPy doesn't provide this, because it's
Hello,
Is there a way to specify a format for the datetime64 constructor? The
constructor doesn't have a doc. I have dates in a file with the format
"MM/dd/YY". datetime64 used to be able to parse these in 1.6.1 but the dev
version throws an error
Hi!
Your Machine should be able to handle at least Mac OS X10.6 and even 10.7.
If there is not a strong reason to remain on 10.5...
10.5 is so long ago, I can barely remember.
cheers,
Samuel
On 01.02.2012, at 18:03, Dustin Lang wrote:
>
> Hi,
>
> I don't really believe this is a numpy bug t
Hi Ruby,
I still do not fully understand your question but what I do in such cases is to
construct a very simple array and test the functions.
The help of numpy.histogram2d or numpy.histogramdd (for more than two dims)
might help here.
So I guess, basically you want to ignore the x,y positions
Hi Hans-Martin!
You could try my instructions recently posted to this list
http://thread.gmane.org/gmane.comp.python.scientific.devel/15956/
Basically, using llvm-gcc scipy segfaults when scipy.test() (on my system at
least).
Therefore, I created the homebrew install formula.
They work for wha
Yes, I agree 100%.
On 26.01.2012, at 10:19, Sturla Molden wrote:
> When we have nice libraries like OpenCL, OpenGL and OpenMP, I am so glad
> we have Microsoft to screw it up.
>
> Congratulations to Redmond: Another C++ API I cannot read, and a
> scientific compute library I hopefully never hav
Sorry for the late answer. But at least for the record:
If you are using eclipse, I assume you have also installed the eclipse plugin
[pydev](http://pydev.org/). Is use it myself, it's good.
Then you have to go to the preferences->pydev->PythonInterpreter and select the
python version you want
I know you wrote that you want "TEXT" files, but never-the-less, I'd like to
point to http://code.google.com/p/h5py/ .
There are viewers for hdf5 and it is stable and widely used.
Samuel
On 24.01.2012, at 00:26, Emmanuel Mayssat wrote:
> After having saved data, I need to know/remember the da
I get the same results as you, Kathy.
*surprised*
(On OS X (Lion), 64 bit, numpy 2.0.0.dev-55472ca, Python 2.7.2.
On 24.01.2012, at 16:29, Kathleen M Tacina wrote:
> I was experimenting with np.min_scalar_type to make sure it worked as
> expected, and found some unexpected results for integers
On 23.01.2012, at 11:23, David Warde-Farley wrote:
>> a = numpy.array(numpy.random.randint(256,size=(500,972)),dtype='uint8')
>> b = numpy.random.randint(500,size=(4993210,))
>> c = a[b]
>> In [14]: c[100:].sum()
>> Out[14]: 0
Same here.
Python 2.7.2, 64bit, Mac OS X (Lion), 8GB RAM,
I'd like to add
http://git.tiker.net/pyopencl.git/blob/HEAD:/examples/demo_mandelbrot.py to the
discussion, since I use pyopencl (http://mathema.tician.de/software/pyopencl)
with great success in my daily scientific computing. Install with pip.
PyOpenCL does understand numpy arrays. You write
I ran into this a while ago and was confused why cov did not behave the way
pierre suggested.
On Jan 21, 2012 12:48 PM, "Elliot Saba" wrote:
> Thank you Sturla, that's exactly what I want.
>
> I'm sorry that I was not able to reply for so long, but Pierre's code is
> similar to what I have alread
[sorry for duplicate - I used the wrong mail address]
I am afraid, I didn't quite get the question.
What is the scenario? What is the benefit that would weight out the performance
hit of checking whether there is a callback or not. This has to be evaluated
quite a lot.
Oh well ... and 1.3.0 is
I would just use a lookup dict:
names = [ "uc_berkeley", "stanford", "uiuc", "google", "intel",
"texas_instruments", "bool"]
lookup = dict( zip( range(len(names)), names ) )
Now, given you have n entries:
S = numpy.zeros( (n, len(names)) ,dtype=numpy.int32)
for k in ["uc_berkeley", "google",
362, in build_msvcr_library
generate_def(dll_file, def_file)
File
"C:\Users\jsalvatier\workspace\numpy\numpy\distutils\mingw32ccompiler.py",
line 282, in generate_def
raise ValueError("Symbol table not found")
ValueError: Symbol table not found
Thank you,
John
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Hellow, while using the nested_iters function, I've noticed that it does
not accept length zero nestings. For example, the following fails:
nested_iters([ones(3),ones(3)], [[], [0]])
with "ValueError: If 'op_axes' or 'itershape' is not NULL in theiterator
constructor, 'oa_ndim' must be greater th
e major changes to f2py in the last two
years?
I appreciate all clues on this issue.
Thank you in advance,
John
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On Thu, Oct 13, 2011 at 5:36 PM, Eric Firing wrote:
>> It would be nice to have a social interface for the mpl gallery like the
>> one similar to the R-gallery
>> [http://www.r-bloggers.com/the-r-graph-gallery-goes-social/]
>
> I think that the priority should go towards massive pruning,
> organi
Thank you John, those are looking useful.
On Thu, Oct 13, 2011 at 2:39 PM, John Hunter wrote:
>
>
>
>
> On Oct 13, 2011, at 4:21 PM, Zachary Pincus
> wrote:
>
> > I keep meaning to use matplotlib as well, but every time I try I also get
> really turned off by
On Oct 13, 2011, at 4:21 PM, Zachary Pincus wrote:
> I keep meaning to use matplotlib as well, but every time I try I also get
> really turned off by the matlabish interface in the examples. I get that it's
> a selling point for matlab refugees, but I find it counterintuitive in the
> same
I second that request.
On Thu, Oct 13, 2011 at 2:21 PM, Zachary Pincus wrote:
> I keep meaning to use matplotlib as well, but every time I try I also get
> really turned off by the matlabish interface in the examples. I get that
> it's a selling point for matlab refugees, but I find it counterint
im -1)
oaxes.insert(axis, out.ndim-1)
oaxes = oaxes[:-1] #remove the now reduced original given axis
out = np.transpose(out, oaxes)
return out
On Mon, Oct 3, 2011 at 2:03 PM, John Salvatier wrote:
> Some observations and questions about nested_iters. Nested_iters seems to
> require that
I just learned two things:
1. np.newaxis
2. Array dimension broadcasting rocks more than you think.
The x[:, np.newaxis] might not be the most intuitive solution but it's great
and powerful.
Intuitive would be to have x.T to transform [0,1,2,4] into [[0],[1],[2],[4]].
Thanks Warren :-)
Samuel
import numpy
# Say y is
y = numpy.array([1,2,3])
Y = numpy.vstack([y,y,y,y])
# Y is array([[1, 2, 3],
# [1, 2, 3],
# [1, 2, 3],
# [1, 2, 3]])
x = numpy.array([[0],[2],[4],[6]]) # a column-vector of your scalars x0, x1...
Y - x
Hope this is what you meant.
cheers,
Sa
do a "grouped" calculation (the group
specified by the group argument) on the values along the given axis. I try
to use nested_iter to iterate over the specified axis and a new axis (the
length of the number of groups) separately so I can do my calculation.
On Mon, Oct 3, 2011 at 9:03 AM,
Thanks mark! I think that's exactly what I'm looking for. We even had a
previous discussion about this (oops!) (
http://mail.scipy.org/pipermail/numpy-discussion/2011-January/054421.html).
I didn't find any documentation, I will try to add some once I understand
how it works better
nctions that operate on arrays and support broadcasting.
Is clearer?
On Fri, Sep 30, 2011 at 5:04 PM, Mark Wiebe wrote:
> On Fri, Sep 30, 2011 at 8:03 AM, John Salvatier > wrote:
>
>> Using nditer, is it possible to manually handle dimensions with different
>> lengths?
>
Using nditer, is it possible to manually handle dimensions with different
lengths?
For example, lets say I had an array A[5, 100] and I wanted to sample every
10 along the second axis so I would end up with an array B[5,10]. Is it
possible to do this with nditer, handling the iteration over the s
Hi!
On 20.09.2011, at 14:41, David Cournapeau wrote:
> On Tue, Sep 20, 2011 at 5:13 AM, Samuel John wrote:
>> Ralf, thanks for your answer.
>>
>> However, in short:
>>
>> I want `pip install numpy; pip install scipy` to work on OS X Lion without
>> extr
Ralf, thanks for your answer.
However, in short:
I want `pip install numpy; pip install scipy` to work on OS X Lion without
extra effort :-)
On 19.09.2011, at 19:05, Ralf Gommers wrote:
> Do you think it's possible to teach numpy to use different CC, CXX?
>
>> This is possible, but numpy pro
Ahoy numpy gurus :-)
Would it be possible to adapt the setup.py and/or numpy/distutils to set the
right variables on Mac OS X 10.7? (see below).
I have looked a bit into the setup.py and the distutils package of numpy but I
am a bit lost.
Do you think it's possible to teach numpy to use differe
Hi Nicolas,
that looks great.
Could you make this available such that `pip install glumpy` would work?
cheers,
Samuel
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middle is returned.
>
> If there are two adjacent elements with the same value,
> one of them is returned.
>
> x[0] and x[-1] are never returned as an index for the
> local maximum.
>
> @Author: Samuel John
> @copyright:
Hi Nils,
which version of numpy, which os?
I can infer that you use python 2.6 in 64bit, right?
Right after the beginning of the numpy.test() are some crucial information.
bests
Samuel
On 14.09.2011, at 22:09, Nils Wagner wrote:
> ERROR: test_polyfit (test_polynomial.TestDocs)
> -
On 06.09.2011, at 22:13, David Cottrell wrote:
> Thanks, I didn't realize dot was not just calling dgemm or some
> variant which I assume would be reasonably fast. I see dgemm appears
> in the numpy code in various places such as the lapack_lite module.
>
> I ran the svd test on the solaris setu
On Wed, Apr 13, 2011 at 8:50 AM, John Hunter wrote:
> On Sat, Jan 15, 2011 at 7:28 AM, Ralf Gommers
> wrote:
>> I've opened http://projects.scipy.org/numpy/ticket/1713 so this doesn't get
>> lost.
>
> Just wanted to bump this -- bug still exists in numpy HEAD
I'm glad datarray is still active. :)
On Thu, May 26, 2011 at 6:36 PM, Craig Yoshioka wrote:
> Thanks, I will. I was just seeing if there was any intention of adding this
> to type of support to numpy directly. It would be faster, and I'm sure it
> would make projects like dataarray much simple
I want to add a question: is there a function that returns the name of the
corresponding C type given the numpy type?
On Sun, May 8, 2011 at 2:45 PM, Keith Goodman wrote:
> I'm writing a function that accepts four possible dtypes: int32,
> int64, float32, float64. The function will call a C exte
On Sat, Jan 15, 2011 at 7:28 AM, Ralf Gommers
wrote:
> I've opened http://projects.scipy.org/numpy/ticket/1713 so this doesn't get
> lost.
Just wanted to bump this -- bug still exists in numpy HEAD 2.0.0.dev-fe3852f
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Hey all, just wanted to let you know that this works nicely:
stacked = np.vstack(MyDict.values())
So long as the dictionary only cotains the recarrays.
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Yes, stacking is fine, and looping per John's suggestion is what I've
done, I was just wondering if there was possibly a more 'pythonic' or
more importantly efficient way than the loop.
Thanks,
john
On Wed, Mar 16, 2011 at 3:38 PM, John Salvatier
wrote:
> I think he wa
I think he wants to stack them (same widths) so stacking them should be
fine.
On Wed, Mar 16, 2011 at 7:30 AM, Bruce Southey wrote:
> On 03/16/2011 08:56 AM, John Salvatier wrote:
>
> Loop through to build a list of arrays, then use vstack on the list.
>
> On Wed, Mar 16, 2011 a
Loop through to build a list of arrays, then use vstack on the list.
On Wed, Mar 16, 2011 at 1:36 AM, John wrote:
> Hello,
>
> I have a dictionary with structured arrays, keyed by integers 0...n.
> There are no other keys in the dictionary.
>
> What is the most efficient
Is there something I can do that would be more efficient than looping
through and using np.concatenate (vstack)?
--john
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The new iteration functionality will be providing this in the near future
(along with many other things). See
https://github.com/numpy/numpy/blob/master/doc/neps/new-iterator-ufunc.rst
On Mon, Mar 14, 2011 at 6:30 PM, Jonathan Taylor <
jonathan.tay...@utoronto.ca> wrote:
> Please excuse the doubl
If they return a tuple of indexes I think 'mulitiindex' sounds quite good.
That is exactly what a multiindex is (
http://en.wikipedia.org/wiki/Multi-index_notation).
On Mon, Mar 14, 2011 at 1:14 AM, Mark Wiebe wrote:
> On Sun, Mar 13, 2011 at 11:59 PM, Ralf Gommers <
> ralf.gomm...@googlemail.co
@Jeff
I need to work with ragged arrays too. Are object arrays of 1d numpy arrays
slower than lists of 1d numpy arrays?
@ Christopher
I'd be interested in hearing if you come up with any better solutions.
On Mon, Mar 7, 2011 at 9:37 AM, Jeff Whitaker wrote:
> On 3/7/11 10:28 AM, Christopher Bar
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