Hi,
Is this intended?
[~/]
[1]: np.result_type(np.uint, np.int)
[1]: dtype('float64')
[~/]
[2]: np.version.version
[2]: '2.0.0.dev-aded70c'
Skipper
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On Tue, Dec 6, 2011 at 7:53 AM, Matthew Brett matthew.br...@gmail.com wrote:
Hi,
On Tue, Dec 6, 2011 at 4:45 AM, Skipper Seabold jsseab...@gmail.com wrote:
Hi,
Is this intended?
[~/]
[1]: np.result_type(np.uint, np.int)
[1]: dtype('float64')
I would guess so - if your system ints
On Mon, Feb 20, 2012 at 1:35 PM, Brett Olsen brett.ol...@gmail.com wrote:
On Sat, Feb 18, 2012 at 8:12 PM, Adam Hughes hugad...@gwmail.gwu.edu wrote:
Hey everyone,
I have timeseries data in which the column label is simply a filename from
which the original data was taken. Here's some sample
On Sat, Feb 25, 2012 at 5:13 PM, Alan G Isaac alan.is...@gmail.com wrote:
On 2/25/2012 4:44 PM, James Bergstra wrote:
bincount([]) makes no sense,
I disagree:
http://permalink.gmane.org/gmane.comp.python.numeric.general/42041
but if a minlength argument is provided,
then the routine
I am surprised by this (though maybe I shouldn't be?) It's always faster to
use list comprehension to unpack lists of tuples than np.array/asarray?
[~/]
[1]: X = [tuple(np.random.randint(10,size=2)) for _ in
range(100)]
[~/]
[2]: timeit np.array([x1 for _,x1 in
X])
1 loops, best of 3: 26.4
Is there a way to use numpy.distuils to programmatically check for a C
compiler at build time in a platform independent way?
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On Wed, Mar 7, 2012 at 12:35 PM, Skipper Seabold jsseab...@gmail.com wrote:
Is there a way to use numpy.distuils to programmatically check for a C
compiler at build time in a platform independent way?
Wading through the numpy/distutils code some more. Would something as
simple as this work all
On Mon, Mar 12, 2012 at 6:04 PM, Abhishek Pratap apra...@lbl.gov wrote:
Hey Guys
Few days with folks at my first pycon has made me wonder how much of
cool things I was missing ..
I am looking to do some quick catch up on numpy and wondering if there
are any set of videos that I can refer
Hi,
I have a pull request here [1] to add a cut function similar to R's
[2]. It seems there are often requests for similar functionality. It's
something I'm making use of for my own work and would like to use in
statstmodels and in generating instances of pandas' Factor class, but
is this
On Mon, Apr 16, 2012 at 5:51 PM, Tony Yu tsy...@gmail.com wrote:
On Mon, Apr 16, 2012 at 5:27 PM, Skipper Seabold jsseab...@gmail.com
wrote:
Hi,
I have a pull request here [1] to add a cut function similar to R's
[2]. It seems there are often requests for similar functionality. It's
On Mon, Apr 16, 2012 at 8:08 PM, Tony Yu tsy...@gmail.com wrote:
On Mon, Apr 16, 2012 at 6:01 PM, Skipper Seabold jsseab...@gmail.com
wrote:
On Mon, Apr 16, 2012 at 5:51 PM, Tony Yu tsy...@gmail.com wrote:
On Mon, Apr 16, 2012 at 5:27 PM, Skipper Seabold jsseab...@gmail.com
wrote
On Wed, Apr 25, 2012 at 12:13 PM, Till Stensitzki mail.t...@gmx.de wrote:
Hello,
is there weighted version of linalg.lstsq available?
In my case, b is a (N,K) matrix, so i can't use manual scaling of x and b.
What shape are the weights in this case? I'm not that familiar with
problems with an
On Wed, May 16, 2012 at 11:50 AM, Robert Kern robert.k...@gmail.com wrote:
On Wed, May 16, 2012 at 4:35 PM, Nathaniel Smith n...@pobox.com wrote:
On Wed, May 16, 2012 at 4:24 PM, Robert Kern robert.k...@gmail.com wrote:
On Wed, May 16, 2012 at 4:21 PM, Nathaniel Smith n...@pobox.com wrote:
I
On Mon, May 21, 2012 at 4:37 PM, Travis Oliphant tra...@continuum.io wrote:
This is the right place to ask, it's just that it can take time to get an
answer because people who might know the answer may not have the time to
respond immediately.
The short answer is that this is not really a
On Tue, Jun 26, 2012 at 7:59 PM, Fernando Perez fperez@gmail.com wrote:
On Tue, Jun 26, 2012 at 1:10 PM, Travis Oliphant tra...@continuum.io wrote:
One issues is the one that Sage identified about the array interface
regression as noted by Jason. Any other regressions from 1.5.x need to
On Mon, Jul 2, 2012 at 9:35 PM, josef.p...@gmail.com wrote:
On Mon, Jul 2, 2012 at 8:08 PM, josef.p...@gmail.com wrote:
On Mon, Jul 2, 2012 at 4:16 PM, Fernando Perez fperez@gmail.com
wrote:
Hi all,
in recent work with a colleague, the need came up for a multivariate
On Sun, Jul 22, 2012 at 2:15 PM, Ralf Gommers
ralf.gomm...@googlemail.com wrote:
Hi,
Just a heads up that right now views of recarrays seem to be problematic,
this doesn't work anymore:
import statsmodels.api as sm
dta = sm.datasets.macrodata.load() # returns a record array with 14
fields
On Tue, Aug 21, 2012 at 3:59 PM, Christoph Gohlke cgoh...@uci.edu wrote:
On 8/21/2012 9:24 AM, Ondřej Čertík wrote:
Hi,
I'm pleased to announce the availability of the first beta release of
NumPy 1.7.0b1.
Sources and binary installers can be found at
On Wed, Nov 21, 2012 at 9:22 PM, Olivier Delalleau sh...@keba.be wrote:
Current behavior looks sensible to me. I personally would prefer no
warning but I think it makes sense to have one as it can be helpful to
detect issues faster.
-=- Olivier
It's configurable.
[~/]
[1]:
I discovered this because scipy.optimize.fmin_powell appears to squeeze 1d
argmin to 0d unlike the other optimizers, but that's a different story.
I would expect the 0d array to behave like the 1d array not the 2d as it
does below. Thoughts? Maybe too big of a pain to change this behavior if
On Wed, Nov 28, 2012 at 12:31 PM, Sebastian Berg sebast...@sipsolutions.net
wrote:
Maybe a strict matrix product would make sense too, but the dot function
behavior cannot be changed in any case, so its pointless to argue about
it. Just make sure your arrays are 2-d (or matrices) if you want
On Thu, Dec 13, 2012 at 12:00 PM, David Cournapeau courn...@gmail.com wrote:
snip
I would even go as far as dropping 2.5 as well then (RHEL 6
uses python 2.6).
+1
Skipper
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On Sun, Jan 13, 2013 at 6:39 PM, Nathaniel Smith n...@pobox.com wrote:
On Sun, Jan 13, 2013 at 11:24 PM, Robert Kern robert.k...@gmail.com
wrote:
On Sun, Jan 13, 2013 at 6:27 PM, Nathaniel Smith n...@pobox.com wrote:
Hi all,
PR 2875 adds two new functions, that generalize zeros(),
On Mon, Feb 25, 2013 at 10:43 AM, Till Stensitzki mail.t...@gmx.de wrote:
First, sorry that i didnt search for an old thread, but because i
disagree with
conclusion i would at least address my reason:
I don't like
np.abs(arr).max()
because I have to concentrate to much on the braces,
On Mon, Mar 18, 2013 at 1:00 PM, Pierre Haessig pierre.haes...@crans.orgwrote:
Hi Sudheer,
Le 14/03/2013 10:18, Sudheer Joseph a écrit :
Dear Numpy/Scipy experts,
Attached is a script which I
made to test the numpy.correlate ( which is called
Some help on this would be greatly appreciated. It's been recommended to
use OpenBlas over ATLAS, so I've been trying to build numpy with openblas
and have run into a few problems.
1) Build fails using bento master and waf 1.7.9, see below.
2) Distutils doesn't seem to be able to find lapack as
mobile device, please excuse my brevity.
On 23.03.2013, at 19:19, Skipper Seabold jsseab...@gmail.com wrote:
Some help on this would be greatly appreciated. It's been recommended to
use OpenBlas over ATLAS, so I've been trying to build numpy with openblas
and have run into a few problems.
1
On Sat, Mar 23, 2013 at 7:26 PM, Ake Sandgren ake.sandg...@hpc2n.umu.se wrote:
On Sat, 2013-03-23 at 14:19 -0400, Skipper Seabold wrote:
Some help on this would be greatly appreciated. It's been recommended
to use OpenBlas over ATLAS, so I've been trying to build numpy with
openblas and have
On Sat, Mar 23, 2013 at 8:44 PM, Skipper Seabold jsseab...@gmail.com wrote:
On Sat, Mar 23, 2013 at 7:26 PM, Ake Sandgren ake.sandg...@hpc2n.umu.se
wrote:
On Sat, 2013-03-23 at 14:19 -0400, Skipper Seabold wrote:
Some help on this would be greatly appreciated. It's been recommended
to use
On Mon, Mar 25, 2013 at 2:40 PM, Dinesh B Vadhia
dineshbvad...@hotmail.comwrote:
**
Caveat: Not tested but it did look interesting:
http://osdf.github.com/blog/numpyscipy-with-openblas-for-ubuntu-1204-second-try.html
.
Would be interested to know if it worked out as want to try out OpenBlas
On Thu, Jul 18, 2013 at 10:49 PM, Yaroslav Halchenko
li...@onerussian.comwrote:
Hi everyone,
Some of my elderly code stopped working upon upgrades of numpy and
upcoming pandas: https://github.com/pydata/pandas/issues/4290 so I have
looked at the code of
2481 def mean(a, axis=None,
On Mon, Aug 19, 2013 at 9:38 AM, Cera, Tim t...@cerazone.net wrote:
On Mon, Aug 19, 2013 at 2:37 AM, Juan Luis Cano juanlu...@gmail.com
wrote:
As now master is open for 1.9, following the discussion opened here
https://github.com/numpy/numpy/issues/2880
it was suggested that we
On Thu, Oct 3, 2013 at 9:10 AM, Benjamin Root ben.r...@ou.edu wrote:
On Thu, Oct 3, 2013 at 6:06 AM, Daniele Nicolodi dani...@grinta.net wrote:
Hello,
sorry, I don't know where exactly jump in in the thread, it is getting
quite long and articulated...
On 02/10/2013 21:19, Charles R Harris
On Mon, Feb 10, 2014 at 2:49 PM, Matthew Brett matthew.br...@gmail.comwrote:
Hi,
On Mon, Feb 10, 2014 at 11:44 AM, josef.p...@gmail.com wrote:
On Mon, Feb 10, 2014 at 2:12 PM, eat e.antero.ta...@gmail.com wrote:
On Mon, Feb 10, 2014 at 9:08 PM, alex argri...@ncsu.edu wrote:
On Sat, Feb 15, 2014 at 5:08 PM, josef.p...@gmail.com wrote:
On Sat, Feb 15, 2014 at 4:56 PM, Sebastian Berg
sebast...@sipsolutions.net wrote:
On Sa, 2014-02-15 at 16:37 -0500, alex wrote:
Hello list,
Here's another idea resurrection from numpy github comments that I've
been advised
Hi,
Should [1] be considered a release blocker for 1.8.1?
Skipper
[1] https://github.com/numpy/numpy/issues/4442
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On Wed, Mar 26, 2014 at 3:48 PM, Slaunger slaun...@gmail.com wrote:
I am working on solving a recent recreational mathematical problem on
Project Euler http://projecteuler.net . I have a solution, which works
fine for small N up to 10^5 but it takes too long to compute for the actual
problem,
On Wed, Mar 26, 2014 at 4:28 PM, Slaunger slaun...@gmail.com wrote:
jseabold wrote
IIUC,
[~/]
[1]: np.logical_and([True, False, True], [False, False, True])
[1]: array([False, False, True], dtype=bool)
You can avoid looping over k since they're all the same length
[~/]
[3]:
On Sat, Oct 9, 2010 at 10:36 PM, josef.p...@gmail.com wrote:
On Sat, Oct 9, 2010 at 10:01 PM, Charles R Harris
charlesr.har...@gmail.com wrote:
On Sat, Oct 9, 2010 at 7:47 PM, josef.p...@gmail.com wrote:
I'm trying to see whether I can do this without reading the full manual.
Is it
On Tue, Oct 12, 2010 at 7:40 AM, Friedrich Romstedt
friedrichromst...@gmail.com wrote:
2010/10/12 Ian Goodfellow goodfellow@gmail.com:
If the arrays are the same size or can be broadcasted to the same
size, it returns true or false on an elementwise basis.
If the arrays are not the same
On Tue, Oct 12, 2010 at 12:32 PM, Robert Kern robert.k...@gmail.com wrote:
On Tue, Oct 12, 2010 at 11:25, Friedrich Romstedt
friedrichromst...@gmail.com wrote:
2010/10/12 Skipper Seabold jsseab...@gmail.com:
Some elaboration here?
http://www.scipy.org/FAQ#head
With names=True, if you specify the dtype manually and specify
usecols, it doesn't grab the correct names along with the columns.
Should be a simple fix, but haven't had time to write a patch yet.
from stringIO import stringIO
import numpy as np
np.__version__
#1.5.0
s =
On Wed, Oct 27, 2010 at 9:37 AM, Johann Cohen-Tanugi
co...@lpta.in2p3.fr wrote:
On 10/27/2010 03:31 PM, Neal Becker wrote:
Johann Cohen-Tanugi wrote:
how about np.any(a!=b) ??
On 10/27/2010 12:25 PM, Neal Becker wrote:
Is there a way to get a short circuit != ?
That is, compare 2
I just ran into this and am kind of baffled. There are other ways I
could do this so it's not a huge deal, but I'm wondering if this is a
bug. I want a (named) structured array with an object dtype. Is this
possible?
For example
In [68]: import numpy as np
In [69]: A =
I am doing some optimizations on random samples. In a small number of
cases, the objective is not well-defined for a given sample (it's not
possible to tell beforehand and hopefully won't happen much in
practice). What is the most numpythonic way to handle this? It
doesn't look like I can use
On Mon, Nov 8, 2010 at 3:14 PM, Skipper Seabold jsseab...@gmail.com wrote:
I am doing some optimizations on random samples. In a small number of
cases, the objective is not well-defined for a given sample (it's not
possible to tell beforehand and hopefully won't happen much in
practice
On Mon, Nov 8, 2010 at 3:42 PM, Bruce Southey bsout...@gmail.com wrote:
On 11/08/2010 02:17 PM, Skipper Seabold wrote:
On Mon, Nov 8, 2010 at 3:14 PM, Skipper Seaboldjsseab...@gmail.com wrote:
I am doing some optimizations on random samples. In a small number of
cases, the objective
On Mon, Nov 8, 2010 at 3:45 PM, Warren Weckesser
warren.weckes...@enthought.com wrote:
On Mon, Nov 8, 2010 at 2:17 PM, Skipper Seabold jsseab...@gmail.com wrote:
On Mon, Nov 8, 2010 at 3:14 PM, Skipper Seabold jsseab...@gmail.com
wrote:
I am doing some optimizations on random samples
On Mon, Nov 8, 2010 at 4:04 PM, Bruce Southey bsout...@gmail.com wrote:
On 11/08/2010 02:52 PM, Skipper Seabold wrote:
On Mon, Nov 8, 2010 at 3:42 PM, Bruce Southeybsout...@gmail.com wrote:
On 11/08/2010 02:17 PM, Skipper Seabold wrote:
On Mon, Nov 8, 2010 at 3:14 PM, Skipper Seaboldjsseab
On Tue, Nov 30, 2010 at 1:34 PM, Keith Goodman kwgood...@gmail.com wrote:
After upgrading from numpy 1.4.1 to 1.5.1 I get warnings like
Warning: invalid value encountered in subtract when I run unit tests
(or timeit) using python -c 'blah' but not from an interactive
session. How can I tell
On Sun, Dec 5, 2010 at 10:44 PM, Wai Yip Tung tungwai...@yahoo.com wrote:
I'm trying to use numpy to manipulate CSV file. I'm looking for feature
similar to relational database. So I come across a class recarray that
seems to meet my need. And then I see other references of structured
array.
On Sun, Dec 5, 2010 at 10:56 PM, Wai Yip Tung tungwai...@yahoo.com wrote:
I'm fairly new to numpy and I'm trying to figure out the right way to do
things. Continuing on my question about using recarray as a relation. I
have a recarray like this
In [339]: arr = np.array([
.: (1,
Am I misreading the docs or missing something? Consider the following
adapted from here:
http://docs.scipy.org/doc/numpy/user/basics.io.genfromtxt.html
from StringIO import StringIO
import numpy as np
data = 1, 2, 3\n4, ,5
np.genfromtxt(StringIO(data), delimiter=,, names=a,b,c,
missing_values=
On Tue, Jan 25, 2011 at 11:17 AM, Pierre GM pgmdevl...@gmail.com wrote:
On Jan 24, 2011, at 11:47 PM, Skipper Seabold wrote:
Am I misreading the docs or missing something? Consider the following
adapted from here:
http://docs.scipy.org/doc/numpy/user/basics.io.genfromtxt.html
from
I get a lot of errors and failures running our tests with most recent
numpy trunk. One in particular (so far) seems to be a bug.
In [1]: import numpy as np
In [2]: np.__version__
Out[2]: '1.6.0.dev-c50af53'
In [3]: tmp_arr = np.array([['black'],['white'],['other']])
In [4]:
On Mon, Feb 21, 2011 at 3:49 PM, Pauli Virtanen p...@iki.fi wrote:
On Mon, 21 Feb 2011 15:09:05 -0500, Skipper Seabold wrote:
[clip]
Should I file a ticket?
Yes.
http://projects.scipy.org/numpy/ticket/1748
[clip]
PS. Is there an incompatibility of numpy 1.5.1 and numpy 1.6.0 trunk
On Wed, Mar 2, 2011 at 5:25 PM, Alex Ter-Sarkissov ater1...@gmail.com wrote:
hi, the question is probably very silly, but can't get my head around it
Say I have an NxM numerical array. What I want is to obtain the row and
column number of the smallest value(kinda like find command in Matlab).
On Sat, Mar 5, 2011 at 9:28 AM, Ralf Gommers
ralf.gomm...@googlemail.com wrote:
On Sat, Mar 5, 2011 at 8:09 AM, Russell E. Owen ro...@uw.edu wrote:
The page http://docs.scipy.org/doc/numpy/user/basics.rec.html
gives a good introduction to structured arrays. However, it says nothing
about how
On Sun, Mar 6, 2011 at 11:12 PM, Ralf Gommers
ralf.gomm...@googlemail.com wrote:
On Sun, Mar 6, 2011 at 1:10 AM, Skipper Seabold jsseab...@gmail.com wrote:
On Sat, Mar 5, 2011 at 9:28 AM, Ralf Gommers
ralf.gomm...@googlemail.com wrote:
On Sat, Mar 5, 2011 at 8:09 AM, Russell E. Owen ro
First consider this example of column_stack
import numpy as np
x = np.random.random((5,1))
y = np.random.random((5,3))
arr = np.column_stack((x[[]], y))
# this fails which is expected
arr = np.column_stack((x[:,[]], y))
# this happily works I guess because
x[:,[]]
# array([], shape=(5, 0),
On Tue, Mar 8, 2011 at 8:08 PM, Skipper Seabold jsseab...@gmail.com wrote:
On Sun, Mar 6, 2011 at 11:12 PM, Ralf Gommers
ralf.gomm...@googlemail.com wrote:
On Sun, Mar 6, 2011 at 1:10 AM, Skipper Seabold jsseab...@gmail.com wrote:
On Sat, Mar 5, 2011 at 9:28 AM, Ralf Gommers
ralf.gomm
On Wed, Mar 9, 2011 at 8:13 PM, Ralf Gommers
ralf.gomm...@googlemail.com wrote:
On Wed, Mar 9, 2011 at 11:24 PM, Skipper Seabold jsseab...@gmail.com wrote:
On Tue, Mar 8, 2011 at 8:08 PM, Skipper Seabold jsseab...@gmail.com wrote:
On Sun, Mar 6, 2011 at 11:12 PM, Ralf Gommers
ralf.gomm
On Wed, Mar 16, 2011 at 2:53 AM, dileep kunjaai dileepkunj...@gmail.com wrote:
Dear sir,
Can we do multiple linear regression(MLR) in python is there any
inbuilt function for MLR
You might be interested in statsmodels
http://statsmodels.sourceforge.net/
Skipper
On Fri, Mar 18, 2011 at 4:27 PM, Rohaq ro...@dearinternet.com wrote:
I've got a CSV file with the following layout:
Location,Result1,Result2
1,0,0
2,0,0
3,1,0
4,1,0
5,1,1
6,0,1
7,0,1
8,0,0
...etc., and I've loaded it using the following:
import numpy as np
data =
On Thu, Mar 24, 2011 at 9:45 AM, Ralf Gommers
ralf.gomm...@googlemail.com wrote:
2011/3/24 Dmitrey tm...@ukr.net:
Hi
2011/3/24 Dmitrey tm...@ukr.net
from numpy import inf, array
inf*0
nan
(ok)
array(inf) * 0.0
StdErr: Warning: invalid value encountered in multiply
nan
My cycled
On Thu, Mar 24, 2011 at 10:52 AM, eat e.antero.ta...@gmail.com wrote:
Hi
On Thu, Mar 24, 2011 at 4:17 PM, Skipper Seabold jsseab...@gmail.com
snip
Also, as Robert pointed out to me before np.errstate is a
context-manager for ignoring these warnings. I often wrap optimization
code
Going through some of the recent threads on similar problems, I'm
trying to discern which is best.
I have X is T x i, theta is T x i x j. I want a T by j array that
contains X[t].T.dot(theta[t]) along axis 0.
Say,
T,i,j = 166,7,3
X = np.random.random((T,i))
theta = np.random.random((T,i,j))
#
On Tue, Apr 5, 2011 at 6:05 PM, Pierre GM pgmdevl...@gmail.com wrote:
On Apr 5, 2011, at 11:52 PM, Ralf Gommers wrote:
On Tue, Apr 5, 2011 at 11:45 PM, Skipper Seabold jsseab...@gmail.com wrote:
On Sun, Apr 3, 2011 at 8:20 PM, Charles R Harris
charlesr.har...@gmail.com wrote:
Should
All,
We noticed some failing tests for statsmodels between numpy 1.5.1 and
numpy = 1.6.0. These are the versions where I noticed the change. It
seems that when you divide a float array and multiply by a boolean
array the answers are different (unless the others are also off by
some floating
On Fri, May 6, 2011 at 11:30 AM, Till Stensitzki mail.t...@gmx.de wrote:
Hi,
discovered another small bug. Windows 7 32 bit, Python 2.6.
In [1]: np.__version__
Out[1]: '1.5.1'
In [2]: a=np.zeros((0,2))
In [3]: np.linalg.qr(a)
** On entry to DGEQRF parameter number 4 had an illegal
On Sun, May 8, 2011 at 11:42 AM, Skipper Seabold jsseab...@gmail.com wrote:
On Fri, May 6, 2011 at 11:30 AM, Till Stensitzki mail.t...@gmx.de wrote:
Hi,
discovered another small bug. Windows 7 32 bit, Python 2.6.
In [1]: np.__version__
Out[1]: '1.5.1'
In [2]: a=np.zeros((0,2))
In [3
On Fri, May 27, 2011 at 12:48 PM, Michael Katz
michaeladamk...@yahoo.com wrote:
I have a numpy array, records, with named fields including a field named
integer_field. I have an array (or list) of values of interest, and I want
to get the indexes where integer_field has any of those values.
On Tue, May 31, 2011 at 9:31 PM, Benjamin Root ben.r...@ou.edu wrote:
On Tue, May 31, 2011 at 8:18 PM, Warren Weckesser
warren.weckes...@enthought.com wrote:
On Tue, May 31, 2011 at 8:08 PM, Charles R Harris
charlesr.har...@gmail.com wrote:
Hi All,
I've been contemplating new functions
On Tue, May 31, 2011 at 9:53 PM, Warren Weckesser
warren.weckes...@enthought.com wrote:
On Tue, May 31, 2011 at 8:36 PM, Skipper Seabold jsseab...@gmail.com
wrote:
I don't know if it's one pass off the top of my head, but I've used
percentile for interpercentile ranges.
[docs]
[1]: X
On Wed, Jun 1, 2011 at 11:31 AM, Mark Miller markperrymil...@gmail.com wrote:
I'd love to see something like a count_unique function included. The
numpy.unique function is handy, but it can be a little awkward to
efficiently go back and get counts of each unique value after the
fact.
Does
On Wed, Jun 1, 2011 at 10:10 PM, Alan G Isaac alan.is...@gmail.com wrote:
On Thu, Jun 2, 2011 at 1:49 AM, Mark Millermarkperrymil...@gmail.com
wrote:
Not quite. Bincount is fine if you have a set of approximately
sequential numbers. But if you don't
On 6/1/2011 9:35 PM, David
On Thu, Jun 2, 2011 at 1:11 PM, Robert Kern robert.k...@gmail.com wrote:
On Thu, Jun 2, 2011 at 12:08, Skipper Seabold jsseab...@gmail.com wrote:
On Wed, Jun 1, 2011 at 10:10 PM, Alan G Isaac alan.is...@gmail.com wrote:
On Thu, Jun 2, 2011 at 1:49 AM, Mark Millermarkperrymil...@gmail.com
Are the testing guidelines included in the HTML docs anywhere? If I
recall, they used to be, and I couldn't find them with a brief
look/google. I'd like to link to them. Maybe the rendered rst page is
considered their new home?
https://github.com/numpy/numpy/blob/master/doc/TESTS.rst.txt
Skipper
On Mon, Jun 20, 2011 at 5:41 PM, Ralf Gommers
ralf.gomm...@googlemail.com wrote:
On Mon, Jun 20, 2011 at 11:36 PM, Skipper Seabold jsseab...@gmail.com
wrote:
Are the testing guidelines included in the HTML docs anywhere? If I
recall, they used to be, and I couldn't find them with a brief
I was just trying to link to the numpy.testing module but can't using
intersphinx. Does anyone know why certain submodules aren't included
in objects.inv? It looks as though it has something to do either with
having a reference at the top of the rst file (so you can :ref: link
to it) or having
On Wed, Jun 29, 2011 at 10:32 AM, Robert Elsner ml...@re-factory.de wrote:
Hello everyone,
I would like to solve the following problem (preferably without
reshaping / flipping the array a).
Assume I have a vector v of length x and an n-dimensional array a where
one dimension has length x
These two cases failed in recfunctions.join_by
1) the case for having either r1postfix or r2postfix as an empty
string was not handled.
2) If there is more than one key and more than variable with a name collision.
Patch and tests in a pull request here: https://github.com/numpy/numpy/pull/100
lib.recfunctions has never been fully advertised. The two bugs I just
discovered lead me to believe that it's not that well vetted, but it
is useful. I can't be the only one using these?
What do people think of either deprecating lib.recfunctions or at
least importing them into the numpy.rec
On Fri, Jul 1, 2011 at 2:22 PM, josef.p...@gmail.com wrote:
On Fri, Jul 1, 2011 at 1:59 PM, Skipper Seabold jsseab...@gmail.com wrote:
lib.recfunctions has never been fully advertised. The two bugs I just
discovered lead me to believe that it's not that well vetted, but it
is useful. I can't
On Fri, Jul 1, 2011 at 3:05 PM, Benjamin Root ben.r...@ou.edu wrote:
On Fri, Jul 1, 2011 at 12:59 PM, Skipper Seabold jsseab...@gmail.com
wrote:
lib.recfunctions has never been fully advertised. The two bugs I just
discovered lead me to believe that it's not that well vetted
On Fri, Jul 1, 2011 at 2:32 PM, Skipper Seabold jsseab...@gmail.com wrote:
On Fri, Jul 1, 2011 at 2:22 PM, josef.p...@gmail.com wrote:
On Fri, Jul 1, 2011 at 1:59 PM, Skipper Seabold jsseab...@gmail.com wrote:
lib.recfunctions has never been fully advertised. The two bugs I just
discovered
On Tue, Jul 5, 2011 at 2:46 PM, Pierre GM pgmdevl...@gmail.com wrote:
On Jul 5, 2011, at 8:33 PM, Skipper Seabold wrote:
On Fri, Jul 1, 2011 at 2:32 PM, Skipper Seabold jsseab...@gmail.com wrote:
On Fri, Jul 1, 2011 at 2:22 PM, josef.p...@gmail.com wrote:
On Fri, Jul 1, 2011 at 1:59 PM
On Wed, Jul 6, 2011 at 7:14 PM, Christopher Jordan-Squire
cjord...@uw.edu wrote:
On Wed, Jul 6, 2011 at 3:47 PM, josef.p...@gmail.com wrote:
On Wed, Jul 6, 2011 at 4:38 PM, josef.p...@gmail.com wrote:
On Wed, Jul 6, 2011 at 4:22 PM, Christopher Jordan-Squire
snip
Mean value replacement, or
2011/7/25 Stéfan van der Walt ste...@sun.ac.za:
On Mon, Jul 25, 2011 at 2:11 PM, Charles R Harris
charlesr.har...@gmail.com wrote:
It's just asking for import problems and general confusion to shadow a
Python module, that's why we renamed io to npyio.
Why? Users can simply do
import
On Tue, Aug 2, 2011 at 3:19 PM, Craig Yoshioka crai...@me.com wrote:
duplicate column in dtype?
Duplicate field names given.? Can you post code to replicate?
I just consolidated some of the columns and the error went away... none had
duplicate field names... hence the question.
I don't
On Tue, Aug 2, 2011 at 4:09 PM, Craig Yoshioka crai...@me.com wrote:
yup, duplicate field names given. I didn't commit the non-working version
and I didn't want to mess up my working code so I tried duplicating the dtype
in a new file and couldn't recreate the error. I suppose the answer
On Wed, Aug 10, 2011 at 3:28 PM, Matthew Brett matthew.br...@gmail.com wrote:
Hi,
I think this one might be for Pauli.
I've run into an odd problem that seems to be an interaction of
numpydoc and autosummary and large classes.
In summary, large classes and numpydoc lead to large tables of
On Thu, Aug 18, 2011 at 10:19 AM, Chris Withers ch...@simplistix.co.uk wrote:
Hi All,
Hopefully a simple newbie question, if I have an array such as :
array([0, 1, 2, 3, 4])
...what's the best way to cummulatively sum it so that I end up with:
array([0, 1, 3, 6, 10])
How would I do this
On Fri, Aug 26, 2011 at 1:10 PM, Mark Janikas mjani...@esri.com wrote:
Hello All,
I am trying to identify columns of a matrix that are perfectly collinear.
It is not that difficult to identify when two columns are identical are have
zero variance, but I do not know how to ID when the
Just ran into this. Any objections for having numpy.std and other
functions in core/fromnumeric.py call asanyarray before trying to use
the array's method? Other data structures like pandas and larry define
their own std method, for instance, and this doesn't allow them to
pass through. I'm
I have installed numpy with my own ATLAS, but trying to install PyMC,
it can't find the ATLAS libs. I also have an older package that
formerly installed but no longer does. I'm being a bit lazy, but am I
missing something? Briefly checking, it looks like the
conventions/assumptions for site.cfg in
On Tue, Oct 11, 2011 at 11:57 AM, Christoph Groth c...@falma.de wrote:
Pauli Virtanen p...@iki.fi writes:
Thank you for your suggestion. It doesn't help me however, because
the algorithm I'm _really_ trying to speed up cannot be vectorized
with numpy in the way you vectorized my toy example.
On Tue, Oct 11, 2011 at 12:41 PM, Christoph Groth c...@falma.de wrote:
Skipper Seabold jsseab...@gmail.com writes:
So it's the dot function being called repeatedly on smallish arrays
that's the bottleneck? I've run into this as well. See this thread
[1].
(...)
Thanks for the links. tokyo
On Thu, Oct 13, 2011 at 6:22 PM, Gökhan Sever gokhanse...@gmail.com wrote:
On Thu, Oct 13, 2011 at 4:15 PM, Benjamin Root ben.r...@ou.edu wrote:
Myself and other developers would greatly appreciate help from the
community to point out which examples are too confusing or out of date. We
It
On Fri, Oct 14, 2011 at 2:18 PM, Alan G Isaac alan.is...@gmail.com wrote:
On 10/14/2011 1:42 PM, josef.p...@gmail.com wrote:
If I remember correctly, signal.lfilter doesn't require stationarity,
but handling of the starting values is a bit difficult.
Hmm. Yes.
AR(1) is trivial, but how
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