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
> 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
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
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
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
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
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
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
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
___
NumPy-Discussion mailing list
Num
jo...@udesktop253:~> gcc --version
gcc (GCC) 3.4.3 (csl-sol210-3_4-branch+sol_rpath)
Copyright (C) 2004 Free Software Foundation, Inc.
This is free software; see the source for copying conditions. There is NO
warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
jo...@udeskt
On Fri, Sep 3, 2010 at 8:50 AM, Benjamin Root wrote:
> Why is this function in matplotlib? Wouldn't it be more useful in numpy?
I tend to add stuff I write to matplotlib. mlab was initially a
repository of matlab-like functions that were not available in numpy
(load, save, linspace, psd, coher
2010/9/3 Guillaume Chérel :
> Great, Thank you. I also found out about csv2rec. I've been missing
> these two a lot.
Some other handy rec functions in mlab
http://matplotlib.sourceforge.net/examples/misc/rec_groupby_demo.html
http://matplotlib.sourceforge.net/examples/misc/rec_join_demo.html
JD
2010/8/16 Guillaume Chérel :
> Hello,
> I'd like to know if there is an easy way to save a list of 1D arrays to a
> csv file, with the first line of the file being the column names.
>
> I found the following, but I can't get to save the column names:
>
> data = rec.array([X1,X2,X3,X4], names=[n1,n
On Fri, Aug 13, 2010 at 3:41 PM, Benjamin Root wrote:
> @Josh: Awesome name. Very fitting...
>
> Another thing that I really love about matplotlib that drove me nuts in
> Matlab was being unable to use multiple colormaps in the same figure.
Funny -- this was one of the *first* things I thought a
On Fri, Aug 13, 2010 at 11:47 AM, David Goldsmith
wrote:
> 2010/7/30 Stéfan van der Walt
>>
>> Hi David
>>
>> Best of luck with your new position! I hope they don't make you program
>> too much MATLAB!
>
> After several years now of writing Python and now having written my first
> on-the-job 15 o
On Thu, Jul 15, 2010 at 7:27 PM, Charles R Harris
wrote:
>
>
> On Thu, Jul 15, 2010 at 6:11 PM, John Hunter wrote:
>>
>> On Thu, Jul 15, 2010 at 6:14 PM, Eric Firing wrote:
>> > Is it certain that the Solaris compiler lacks isinf? Is it possible
>> &
On Thu, Jul 15, 2010 at 7:11 PM, John Hunter wrote:
> On Thu, Jul 15, 2010 at 6:14 PM, Eric Firing wrote:
>> Is it certain that the Solaris compiler lacks isinf? Is it possible
>> that it has it, but it is not being detected?
>
> Just to clarify, I'm not using the sun
On Thu, Jul 15, 2010 at 6:14 PM, Eric Firing wrote:
> Is it certain that the Solaris compiler lacks isinf? Is it possible
> that it has it, but it is not being detected?
Just to clarify, I'm not using the sun compiler, but gcc-3.4.3 on solaris x86
___
I am seeing a problem on Solaris since I upgraded to svn HEAD.
np.isinf does not handle np.inf. See ipython session below. I am not
seeing this problem w/ HEAD on an ubuntu linux box I tested on
In [1]: import numpy as np
In [2]: np.__version__
Out[2]: '2.0.0.dev8480'
In [3]: x = np.inf
np.inf
I use record arrays extensively with python datetimes, which works if
you pass in a list of lists of data with the names. numpy can
accurately infer the dtypes and create a usable record array. Eg,
import datetime
import numpy as np
rows = [ [datetime.date(2001,1,1), 12, 23.],
On Fri, Jul 9, 2010 at 8:03 PM, Peter Isaac wrote:
> Note that EPD-6.2-2 works fine with this script on WinXP.
> Any suggestions welcome
then just use epd-6.2.2 on winxp.
your-mpl-developer-channeling-steve-jobs,
JDH
___
NumPy-Discussion mailing lis
On Tue, Jun 8, 2010 at 10:33 AM, Sebastian Haase wrote:
> On Tue, Jun 8, 2010 at 5:23 PM, David Goldsmith
> wrote:
>> On Tue, Jun 8, 2010 at 12:10 AM, Sebastian Haase
>> wrote:
>>>
>>> I don't want to complain
>>> But what is wrong with a limit of 40kB ? There are enough places where
>>> o
On Mon, Mar 8, 2010 at 11:39 PM, Charles R Harris
wrote:
>> - port matplotlib to Py3K
We'd be happy to mentor a project here. To my knowledge, nothing has
been done, other than upgrade to CXX6 (our C++ extension lib). Most,
but not all, of our extension code is exposed through CXX, which as of
On Wed, Feb 10, 2010 at 8:54 AM, John Hunter wrote:
> On Tue, Feb 9, 2010 at 7:53 PM, Pierre GM wrote:
>> On Feb 9, 2010, at 8:16 PM, John Hunter wrote:
>
>>> and have "totxt", "tocsv". etc... from rec2txt, rec2csv, etc... I
>>> think the func
On Tue, Feb 9, 2010 at 7:53 PM, Pierre GM wrote:
> On Feb 9, 2010, at 8:16 PM, John Hunter wrote:
>> and have "totxt", "tocsv". etc... from rec2txt, rec2csv, etc... I
>> think the functionality of mlab.rec_summarize and rec_groupby is very
>> useful, bu
On Tue, Feb 9, 2010 at 7:02 PM, Pierre GM wrote:
> On Feb 9, 2010, at 7:54 PM, Pauli Virtanen wrote:
>>
>> But, should we make these functions available under some less
>> internal-ish namespace? There's numpy.rec at the least -- it could be
>> made a real module to pull in things from core and li
On Tue, Feb 9, 2010 at 4:43 PM, Fernando Perez wrote:
> On Tue, Feb 9, 2010 at 5:02 PM, Robert Kern wrote:
>>
>> numpy.lib.recfunctions.join_by(key, r1, r2, jointype='leftouter')
>>
>
> And if that isn't sufficient, John has in matplotlib.mlab a few other
> similar utilities that allow for more c
We are looking to hire a quantitative researcher to help research and
develop trading ideas, and to develop and support infrastructure to
put these trading strategies into production. We are looking for
someone who is bright and curious with a quantitative background and a
strong interest in writi
On Wed, Nov 25, 2009 at 8:48 AM, Dan Yamins wrote:
> Am I just not supposed to be working with length-0 string columns, period?
But why would you want to? array dtypes are immutable, so you are
saying: I want this field to be only empty strings now and forever.
So you can't initialize them to b
toolbar? It keeps a ref to the canvas. If you
can create a small freestanding example, that would help
-Mathew
On Thu, Nov 19, 2009 at 10:42 AM, John Hunter
wrote:
On Nov 19, 2009, at 12:35 PM, Mathew Yeates
wrote:
Yeah, I tried that.
Here's what I'm doing. I have an a
ular references. Pyplot close does this
automatically, but this does not apply to embedding.
How are you running you app? From the shell or IPython?
Mathew
On Thu, Nov 19, 2009 at 10:30 AM, John Hunter
wrote:
On Nov 19, 2009, at 11:57 AM, Robert Kern
wrote:
> On Thu, Nov
On Nov 19, 2009, at 11:57 AM, Robert Kern wrote:
> On Thu, Nov 19, 2009 at 11:52, Mathew Yeates
> wrote:
>> There is definitely something wrong with matplotlib/numpy. Consider
>> the
>> following
>>> from numpy import *
>>> mydata=memmap('map.dat',dtype=float64,mode='w+',shape=56566500)
I just tracked down a subtle bug in my code, which is equivalent to
In [64]: x, y = np.random.rand(2, n)
In [65]: z = np.zeros_like(x)
In [66]: mask = x>0.5
In [67]: z[mask] = x/y
I meant to write
z[mask] = x[mask]/y[mask]
so I can fix my code, but why is line 67 allowed
In [68]: z[m
On Wed, Aug 12, 2009 at 6:28 AM, John Hunter wrote:
> We would like to add function plotting to mpl, but to do this right we
> need to be able to adaptively sample a function evaluated over an
> interval so that some tolerance condition is satisfied, perhaps with
> both a relative
We would like to add function plotting to mpl, but to do this right we
need to be able to adaptively sample a function evaluated over an
interval so that some tolerance condition is satisfied, perhaps with
both a relative and absolute error tolerance condition. I am a bit
out of my area of compete
yubnub is pretty cool -- it's a command line interface for the web.
You can enable it in firefox by typing "about:config" in the URL bar,
scrolling down to "keyword.URL", right click on the line and choose
modify, and set the value to be
http://www.yubnub.org/parser/parse?default=g2&command=
Then
2009/5/20 Stéfan van der Walt :
> David Cournapeau also put a check in place so that the NumPy build
> will break if we forget to update the API version again.
>
> So, while we can't change the releases of NumPy out there already, we
> can at least ensure that this won't happen again.
OK, great -
We are trying to build and test mpl installers for python2.4, 2.5 and
2.6. What we are finding is that if we build mpl against a more
recent numpy than the installed numpy on a test machine, the import of
mpl extension modules which depend on numpy trigger a segfault.
Eg, on python2.5 and python2
A colleague of mine has a bunch of numpy arrays saved with np.save and
he now wants to access them directly in C, with or w/o the numpy C API
doesn't matter. Does anyone have any sample code lying around which
he can borrow from? The array is a structured array with an otherwise
plain vanilla dty
Andrew, since you are the original author of the isnan port, could you
patch the branch and the trunk to take care of this?
JDH
On Fri, Jan 16, 2009 at 8:07 AM, George wrote:
> Hello.
>
> I am terribly sorry. I was mistaken last night. I had the latest Matplotlib
> version 0.98.5.2 and I thought
On Thu, Jan 8, 2009 at 12:34 PM, Eric Firing wrote:
> John Hunter wrote:
>> On Wed, Jan 7, 2009 at 5:37 PM, Eric Firing wrote:
>>
>>> A couple small changes speed it up quite a bit:
>>>
>>> efir...@manini:~/temp/nnbf$ python test_nnbf.py
>>>
On Wed, Jan 7, 2009 at 5:37 PM, Eric Firing wrote:
> A couple small changes speed it up quite a bit:
>
> efir...@manini:~/temp/nnbf$ python test_nnbf.py
> loading data... this could take a while
> testing nnbf...
>10 trials: mean=0.0150, min=0.0100
> testing numpy...
>10 trials: mean=0.
Partly as an excuse to learn cython, and partly because I need to eke
out some extra performance of a neighborhood search, I tried to code
up a brute force neighborhood search in cython around an N-dimensional
point p. I need to incrementally add a point, do a search, add
another point, do another
On Wed, Jan 7, 2009 at 6:37 AM, Franck Pommereau
wrote:
> def f4 (x, y) :
>"""Jean-Baptiste Rudant
>
>test 1 CPU times: 111.21s
>test 2 CPU times: 13.48s
>
>As Jean-Baptiste noticed, this solution is not very efficient (but
>works almost of-the-shelf).
>"""
>recXY = n
On Tue, Jan 6, 2009 at 7:38 AM, Jean-Baptiste Rudant
wrote:
> Hello,
> I'm not an expert. Something exists in matplotlib, but it's not very
> efficient.
> import matplotlib.mlab
> import numpy
> N = 1000
> X = numpy.random.randint(0, 10, N)
> Y = numpy.random.random(N)
> recXY = numpy.rec.fromarr
On Fri, Dec 19, 2008 at 4:30 PM, Ondrej Certik wrote:
> while packaging the new version of numpy, I realized that it is
> missing a documentation. I just checked with Stefan on Jabber and he
> thinks
> it should be rather a trivial fix. Do you Jarrod think you could
> please release a new tarball
On Fri, Dec 19, 2008 at 12:59 PM, Eric Firing wrote:
> Licensing is no problem; I have never bothered with it, but I can tack on a
> BSD-type license if that would help.
Great -- if you are the copyright holder, would you commit a BSD
license file to the py4science trailstats dir? I just commit
On Thu, Dec 18, 2008 at 8:27 PM, Bradford Cross
wrote:
> This is a new project I just released.
>
> I know it is C#, but some of the design and idioms would be nice in
> numpy/scipy for working with discrete event simulators, time series, and
> event stream processing.
>
> http://code.google.com/p
On Mon, Dec 1, 2008 at 1:14 PM, Pierre GM <[EMAIL PROTECTED]> wrote:
>> The problem you have is that the default dtype is 'float' (for
>> backwards compatibility w/ the original np.loadtxt). What you want
>> is to automatically change the dtype according to the content of
>> your file: you should
On Mon, Dec 1, 2008 at 12:21 PM, Pierre GM <[EMAIL PROTECTED]> wrote:
> Well, looks like the attachment is too big, so here's the implementation.
> The tests will come in another message.\
It looks like I am doing something wrong -- trying to parse a CSV file
with dates formatted like '2008-10-14
On Tue, Nov 25, 2008 at 11:23 PM, Ryan May <[EMAIL PROTECTED]> wrote:
> Updated patch attached. This includes:
> * Updated docstring
> * New tests
> * Fixes for previous issues
> * Fixes to make new tests actually work
>
> I appreciate any and all feedback.
I'm having trouble applying your p
On Tue, Nov 25, 2008 at 2:01 PM, Pierre GM <[EMAIL PROTECTED]> wrote:
>
> On Nov 25, 2008, at 2:26 PM, John Hunter wrote:
>>
>> Yes, I've said on a number of occasions I'd like to see these
>> functions in numpy, since a number of them make more sense
On Tue, Nov 25, 2008 at 12:16 PM, Pierre GM <[EMAIL PROTECTED]> wrote:
> A la mlab.csv2rec ? It could work with a bit more tweaking, basically
> following John Hunter's et al. path. What happens when the column names are
> unknown (read from the header) or wrong ?
>
> Actually, I'd like John to co
I frequently want to break a 1D array into regions above and below
some threshold, identifying all such subslices where the contiguous
elements are above the threshold. I have two related implementations
below to illustrate what I am after. The first "crossings" is rather
naive in that it doesn't
On Thu, Oct 16, 2008 at 2:28 PM, Rob Hetland <[EMAIL PROTECTED]> wrote:
> I did not know that very useful thing. But now I do. This is solid
> proof that lurking on the mailing lists makes you smarter.
and that our documentation effort still has a long way to go !
FAQ added at
http://matplotli
On Thu, Oct 16, 2008 at 1:25 PM, Rob Hetland <[EMAIL PROTECTED]> wrote:
> This question gets asked about once a month on the mailing list.
> Perhaps pnpoly could find a permanent home in scipy? (or somewhere?)
> Obviously, many would find it useful.
It is already in matplotlib
In [1]: import mat
On Mon, Oct 13, 2008 at 2:29 PM, Alan G Isaac <[EMAIL PROTECTED]> wrote:
> The problem is, you did not just ask
> for technical information. You also
> accused people of being condescending
> and demeaning. But nobody was
> condescending or demeaning. As several
> people **politely** explained
On Mon, Sep 22, 2008 at 10:23 AM, Robert Kern <[EMAIL PROTECTED]> wrote:
> On Mon, Sep 22, 2008 at 10:22, Robert Kern <[EMAIL PROTECTED]> wrote:
>
>> ind2mark = np.asarray((ind[:,np.newaxis] + np.arange(Nmark).flat).clip(0,
>> N-1)
>> marked[ind2mark] = True
>
> Missing parenthesis:
>
> ind2mark =
On Mon, Sep 22, 2008 at 10:13 AM, Robert Kern <[EMAIL PROTECTED]> wrote:
> marked[ind + np.arange(Nmark)] = True
That triggers a broadcasting error:
Traceback (most recent call last):
File "/home/titan/johnh/test.py", line 13, in ?
marked3[ind + np.arange(Nmark)] = True
ValueError: shape m
I have a an array of indices into a larger array where some condition
is satisfied. I want to create a larger set of indices which *mark*
all the indicies following the condition over some Nmark length
window. In code:
import numpy as np
N = 1000
Nmark = 20
ind = np.nonzero(np.r
On Mon, Jul 28, 2008 at 2:35 PM, Robert Kern <[EMAIL PROTECTED]> wrote:
> Both, if the behavior exhibits itself without the npy file. If it only
> exhibits itself with an npy involved, then we have some more
> information about where the problem might be.
OK, I'll see what I can come up with. In
On Mon, Jul 28, 2008 at 2:02 PM, Robert Kern <[EMAIL PROTECTED]> wrote:
> On Mon, Jul 28, 2008 at 13:56, John Hunter <[EMAIL PROTECTED]> wrote:
>> In trying to track down a bug in matplotlib, I have come across tsome
>> very strange numpy behavior. Basically, whether
In trying to track down a bug in matplotlib, I have come across tsome
very strange numpy behavior. Basically, whether or not I call
np.seterr('raise') or not in a matplotlib demo affects the behavior of
seterr in another (pure numpy) script, run in a separate process.
Something about the numpy sta
On Fri, Jul 25, 2008 at 8:22 PM, Matt Knox <[EMAIL PROTECTED]> wrote:
> The automatic string parsing has been mentioned before, but it is a feature
> I am personally very fond of. I use it all the time, and I suspect a lot of
> people would like it very much if they used it. It's not suited for hi
On Mon, Jul 14, 2008 at 12:34 PM, Robert Kern <[EMAIL PROTECTED]> wrote:
> We're not doing anything special, here. When I install using "sudo
> python install.py" on OS X, all of the permissions are 644. I think
> the problem may be in your pipeline.
With a little more testing, what I am finding
I have a rather unconventional install pipeline at work and owner only
read permissions on a number of the tests are causing me minor
problems. It appears the permissions on the tests are set rather
inconsistently in numpy and python -- is there any reason not to make
these all 644?
[EMAIL PROTEC
On Fri, Jul 11, 2008 at 1:14 PM, Francesc Alted <[EMAIL PROTECTED]> wrote:
> So, it seems that setters/getters for matplotlib datetime could be
> supported, maybe at the risk of loosing precision. We should study
> this more carefully, but I suppose that if there is interest enough
> that could b
I would like to find the sample points where the running sum of some
vector exceeds some threshold -- at those points I want to collect all
the data in the vector since the last time the criteria was reached
and compute some stats on it. For example, in python
tot = 0.
xs = []
ys = []
On Thu, Jun 26, 2008 at 11:38 AM, Travis E. Oliphant
<[EMAIL PROTECTED]> wrote:
> Stéfan van der Walt wrote:
>> Hi all,
>>
>> I am documenting `recarray`, and have a question:
>>
>> Is its use still recommended, or has it been superseded by fancy data-types?
>>
> I rarely recommend it's use (but so
On Sat, May 31, 2008 at 4:05 AM, R. Bastian <[EMAIL PROTECTED]> wrote:
>> Neat! I really like the layout. The red format warnings are a nice touch:
>> http://sd-2116.dedibox.fr/pydocweb/doc/numpy.core.umath.exp/
Hi, I was just reading through this example when I noticed this usage:
from matp
I just spent a while tracking down a bug in my code, and found out the
problem was numpy was letting me get away with using a logical mask of
smaller size than the array it was masking.
In [19]: x = np.random.rand(10)
In [20]: x
Out[20]:
array([ 0.72253623, 0.8412243 , 0.12835194, 0.01
On Tue, May 20, 2008 at 12:13 PM, Charles R Harris
<[EMAIL PROTECTED]> wrote:
> Looks like we need to add a test for this before release. But I'm off to
> work.
Here's a simpler example in case you want to wrap it in a test harness:
import datetime
import numpy as np
r = np.rec.fromarrays([
I have a record array w/ dates (O4) and floats. If some of these
floats are NaN, np.save crashes (on my solaris platform but not on a
linux machine I tested on). Here is the code that produces the bug:
In [1]: pwd
Out[1]: '/home/titan/johnh/python/svn/matplotlib/matplotlib/examples/data'
In [2]
[apologies if this is a resend, my mail just flaked out]
I have a boolean array and would like to find the lowest index "ind"
where N contiguous elements are all True. Eg, if x is
In [101]: x = np.random.rand(20)>.4
In [102]: x
Out[102]:
array([False, True, True, False, False, True, True, F
We recently deprecated matplotlib.mlab.hist, and I am now hitting a
bug in numpy's historgram, which appears to be caused by the use of
"any" that does not exist in the namespace. Small patch attached.
The example below exposes the bug:
Python 2.4.2 (#1, Feb 23 2006, 12:48:31)
Type "copyright", "
Apologies for the off-topic post to the numpy list, but we have just
committed some potentially code-breaking changes to the matplotlib svn
repository, and we want to gve as wide a notification to people as
possible. Please do not reply to the numpy list, but rather to a
matplotlib mailing list .
On Dec 3, 2007 12:00 PM, Zachary Pincus <[EMAIL PROTECTED]> wrote:
> Thanks -- I hadn't realized matplotlib's user-interaction abilities
> were that sophisticated! I'll definitely give that route a shot.
Here is another example which will help you understand how to do
interaction. You can drag t
On Nov 6, 2007 8:22 AM, Lisandro Dalcin <[EMAIL PROTECTED]> wrote:
> Mmm...
> It looks as it 'mask' is being inernally converted from
> [True, False, False, False, True]
> to
> [1, 0, 0, 0, 1]
Yep, clearly. The question is: is this the desired behavior because
it leads to a "silent failure" for p
A colleague of mine just asked for help with a pesky bug that turned
out to be caused by his use of a list of booleans rather than an array
of booleans as his logical indexing mask. I assume this is a feature
and not a bug, but it certainly surprised him:
In [58]: mask = [True, False, False, Fals
In financial time series, it is very common to keep track of things
like a trailing N day max, trailing N day average, etc. Generally,
for a 1D array x, I'd like to be able to efficiently compute a new
len(x) vector where y[i] = func(x[i-N:]) and I need to be able to
handle edge effects (eg where
I am working on an example to illustrate convolution in the temporal
and spectral domains, using the property that a convolution in the
time domain is a multiplication in the fourier domain. I am using
numpy.fft and numpy.convolve to compute the solution two ways, and
comparing them. I am getting
On 9/26/07, Robert Kern <[EMAIL PROTECTED]> wrote:
> Here is the straightforward way:
>
> In [15]: import numpy as np
>
> In [16]: dt = np.dtype([('foo', int), ('bar', float)])
>
> In [17]: r = np.zeros((3,3), dtype=dt)
Here is a (hopefully) simple question. If I create an array like
this, how c
I have a record array r and I want to add a new field to it. I have
been looking at setfield but I am not sure how to use it for this
purpose. Eg
# r is some npy record array
N = len(r)
x = npy.zeros(N)
# add array of floats x to r with dtype name 'jdh' and type 'http://projects.scipy.org/mailma
Is it desirable that numpy.corrcoef for two arrays returns a 2x2 array
rather than a scalar
In [10]: npy.corrcoef(npy.random.rand(10), npy.random.rand(10))
Out[10]:
array([[ 1., -0.16088728],
[-0.16088728, 1.]])
I always end up extracting the 0,1 element anyway. What is
On 8/24/07, Travis Oliphant <[EMAIL PROTECTED]> wrote:
> I like the direction of this work. For me, the biggest issue is whether
> or not matplotlib (and other code depending on numpy.ma) works with it.
> I'm pretty sure this can be handled and so, I'd personally like to see it.
mpl already suppo
On 7/6/07, Vincent Nijs <[EMAIL PROTECTED]> wrote:
> I wrote the attached (small) program to read in a text/csv file with
> different data types and convert it into a recarray without having to
> pre-specify the dtypes or variables names. I am just too lazy to type-in
> stuff like that :) The suppo
I can create a record array with datetime types using fromrecords if I
don't specify a dtype and let numpy determine the dtype. But when I
try and set the dtype at record array creation time, I get the error
below
In [17]: import numpy
In [18]: import datetime
In [19]: dt = datetime.datetime
I
On 6/13/07, Pierre GM <[EMAIL PROTECTED]> wrote:
> Have you tried mrecords, in the alternative maskedarray package available on
> the scipy SVN ? It should support masked fields (by opposition to masked
> records in numpy.core.ma). If not, would you mind giving a test and letting
> me know your su
I fund myself using record arrays more and more, and feature missing
is the ability to do tab completion on attribute names in ipython,
presumably because you are using a dict under the hood and __getattr__
to resolve
o.key
where o is a record array and key is a field name.
How hard would it be
On 6/12/07, Robert Kern <[EMAIL PROTECTED]> wrote:
> John Hunter wrote:
> > Do record arrays support masks?
>
> I believe so, but not individual masks for each component in the record.
I see, too bad. I am working on the matplotlib.mlab.csv2rec function
and need to handle mi
Do record arrays support masks?
JDH
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On 5/31/07, Matthew Brett <[EMAIL PROTECTED]> wrote:
> Hi,
>
> > That would get them all built as a cohesive set. Then I'd repeat the
> > installs without PYTHONPATH:
>
> Is that any different from:
> cd ~/src
>cd numpy
>python setup.py build
>cd ../scipy
>python setup.py build
We
A colleague of mine is trying to update our production environment
with the latest releases of numpy, scipy, mpl and ipython, and is
worried about the lag time when there is a new numpy and old scipy,
etc... as the build progresses. This is the scheme he is considering,
which looks fine to me, but
I have a numpy record array and I want to pretty print a single
element. I was trying to loop over the names in the element dtype and
use getattr to access the field value, but I got fouled up because
getattr is trying to access the dtype attribute of one of the python
objects (datetime.date) that
On 4/25/07, Fernando Perez <[EMAIL PROTECTED]> wrote:
> Since authors are allowed by their publication policy to keep a
> publicly available copy of their papers on their personal website,
> here's the ipython one:
Didn't know that... here's a link to my matplotlib article
http://nitace.bsd.uchi
I have a numpy array of floats, and would like an easy way of
specifying the format string when printing the array, eg
print x.pprint('%1.3f')
would do the normal repr of the array but using my format string for
the individual elements. Is there and easy way to get something like
this currently?
> "David" == David Cournapeau <[EMAIL PROTECTED]> writes:
David> Of this 300 ms spent in Colormap functor, 200 ms are taken
David> by the take function: this is the function which I think
David> can be speed up considerably.
Sorry I had missed this in the previous conversations.
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