Re: [Numpy-discussion] ANN: pandas v0.18.0rc1 - RELEASE CANDIDATE

On 15 Feb 2016, at 6:55 pm, Jeff Reback wrote: > > https://github.com/pydata/pandas/releases/tag/v0.18.0rc1 Ah, think I forgot about the ‘releases’ pages. Built on OS X 10.10 + 10.11 with python 2.7.11, 3.4.4 and 3.5.1. 17 errors in the test suite + 1 failure with

Re: [Numpy-discussion] ANN: pandas v0.18.0rc1 - RELEASE CANDIDATE

On 14 Feb 2016, at 1:53 am, Jeff Reback wrote: > > I'm pleased to announce the availability of the first release candidate of > Pandas 0.18.0. > Please try this RC and report any issues here: Pandas Issues > We will be releasing officially in 1-2 weeks or so. > Thanks,

Re: [Numpy-discussion] Numpy 1.11.0b1 is out

> On 31 Jan 2016, at 9:48 am, Sebastian Berg <sebast...@sipsolutions.net> wrote: > > On Sa, 2016-01-30 at 20:27 +0100, Derek Homeier wrote: >> On 27 Jan 2016, at 1:10 pm, Sebastian Berg < >> sebast...@sipsolutions.net> wrote: >>> >>> O

Re: [Numpy-discussion] Numpy 1.11.0b1 is out

On 27 Jan 2016, at 1:10 pm, Sebastian Berg wrote: > > On Mi, 2016-01-27 at 11:19 +, Nadav Horesh wrote: >> Why the dot function/method is slower than @ on python 3.5.1? Tested >> from the latest 1.11 maintenance branch. >> > > The explanation I think is that you

Re: [Numpy-discussion] [SciPy-Dev] Numpy 1.11.0b1 is out

On 27 Jan 2016, at 2:58 AM, Charles R Harris wrote: > > FWIW, the maintenance/1.11.x branch (there is no tag for the beta?) builds > and passes all tests with Python 2.7.11 > and 3.5.1 on Mac OS X 10.10. > > > You probably didn't fetch the tags, if they can't be

Re: [Numpy-discussion] [SciPy-Dev] Numpy 1.11.0b1 is out

Hi Chuck, > I'm pleased to announce that Numpy 1.11.0b1 is now available on sourceforge. > This is a source release as the mingw32 toolchain is broken. Please test it > out and report any errors that you discover. Hopefully we can do better with > 1.11.0 than we did with 1.10.0 ;) the tarball

Re: [Numpy-discussion] performance solving system of equations in numpy and MATLAB

On 16 Dec 2015, at 8:22 PM, Matthew Brett wrote: > >>> In [4]: %time testx = np.linalg.solve(testA, testb) >>> CPU times: user 1min, sys: 468 ms, total: 1min 1s >>> Wall time: 15.3 s >>> >>> >>> so, it looks like you will need to buy a MKL license separately (which >>>

Re: [Numpy-discussion] deprecate fromstring() for text reading?

On 3 Nov 2015, at 6:03 pm, Chris Barker - NOAA Federal wrote: > > I was more aiming to point out a situation where the NumPy's text file reader > was significantly better than the Pandas version, so we would want to make > sure that we properly benchmark any significant

Re: [Numpy-discussion] ANN: HDF5 for Python 2.5.0

On 9 Apr 2015, at 9:41 pm, Andrew Collette andrew.colle...@gmail.com wrote: Congrats! Also btw, you might want to switch to a new subject line format for these emails -- the mention of Python 2.5 getting hdf5 support made me do a serious double take before I figured out what was going on, and

Re: [Numpy-discussion] Memory efficient alternative for np.loadtxt and np.genfromtxt

On 26 Oct 2014, at 02:21 pm, Eelco Hoogendoorn hoogendoorn.ee...@gmail.com wrote: Im not sure why the memory doubling is necessary. Isnt it possible to preallocate the arrays and write to them? I suppose this might be inefficient though, in case you end up reading only a small subset of

Re: [Numpy-discussion] Changed behavior of np.gradient

On 4 Oct 2014, at 08:37 pm, Ariel Rokem aro...@gmail.com wrote: import numpy as np np.__version__ '1.9.0' np.gradient(np.array([[1, 2, 6], [3, 4, 5]], dtype=np.float)) [array([[ 2., 2., -1.], [ 2., 2., -1.]]), array([[-0.5, 2.5, 5.5], [ 1. , 1. , 1. ]])] On the

Re: [Numpy-discussion] Changed behavior of np.gradient

Hi Ariel, I think that the docstring in 1.9 is fine (has the 1.9 result). The docs online (for all of numpy) are still on version 1.8, though. I think that enabling the old behavior might be useful, if only so that I can write code that behaves consistently across these two versions of

Re: [Numpy-discussion] Bug in genfromtxt with usecols and converters

On 26 Aug 2014, at 09:05 pm, Adrian Altenhoff adrian.altenh...@inf.ethz.ch wrote: But you are right that the problem with using the first_values, which should of course be valid, somehow stems from the use of usecols, it seems that in that loop for (i, conv) in user_converters.items():

Re: [Numpy-discussion] Bug in genfromtxt with usecols and converters

Hi Adrian, I tried to load data from a csv file into numpy using genfromtxt. I need only a subset of the columns and want to apply some conversions to the data. attached is a minimal script showing the error. In brief, I want to load columns 1,2 and 4. But in the converter function for the

Re: [Numpy-discussion] Bug in genfromtxt with usecols and converters

Hi Adrian, not sure whether to call it a bug; the error seems to arise before reading any actual data (even on reading from an empty string); when genfromtxt is checking the filling_values used to substitute missing or invalid data it is apparently testing on default testing values of 1

Re: [Numpy-discussion] ANN: NumPy 1.8.2 release candidate

On 5 Aug 2014, at 11:27 pm, Matthew Brett matthew.br...@gmail.com wrote: OSX wheels built and tested and uploaded OK : http://wheels.scikit-image.org https://travis-ci.org/matthew-brett/numpy-atlas-binaries/builds/31747958 Will test against the scipy stack later on today. Built and

Re: [Numpy-discussion] length - sticks algorithm

On 29 Jul 2014, at 02:43 pm, Robert Kern robert.k...@gmail.com wrote: On Tue, Jul 29, 2014 at 12:47 PM, Josè Luis Mietta joseluismie...@yahoo.com.ar wrote: Robert, thanks for your help! Now I have: * Q nodes (Q stick-stick intersections) * a list 'NODES'=[(x,y,i,j)_1,,

Re: [Numpy-discussion] problems with mailing list ?

On 18 Jul 2014, at 01:07 pm, josef.p...@gmail.com wrote: Are the problems with sending out the messages with the mailing lists? I'm getting some replies without original messages, and in some threads I don't get replies, missing part of the discussions. There seem to be problems with the

[Numpy-discussion] genfromtxt universal newline support

Hi all, I was just having a new look into the mess that is, imo, the support for automatic line ending recognition in genfromtxt, and more generally, the Python file openers. I am glad at least reading gzip files is no longer entirely broken in Python3, but actually detecting in particular

Re: [Numpy-discussion] genfromtxt universal newline support

On 30 Jun 2014, at 04:39 pm, Nathaniel Smith n...@pobox.com wrote: On Mon, Jun 30, 2014 at 12:33 PM, Julian Taylor jtaylor.deb...@googlemail.com wrote: genfromtxt and loadtxt need an almost full rewrite to fix the botched python3 conversion of these functions. There are a couple threads

Re: [Numpy-discussion] genfromtxt universal newline support

On 30 Jun 2014, at 04:56 pm, Nathaniel Smith n...@pobox.com wrote: A real need, which had also been discussed at length, is a truly performant text IO function (i.e. one using a compiled ASCII number parser, and optimally also a more memory-efficient one), but unfortunately all people

Re: [Numpy-discussion] genfromtxt universal newline support

On 30.06.2014, at 23:10, Jeff Reback jeffreb...@gmail.com wrote: In pandas 0.14.0, generic whitespace IS parsed via the c-parser, e.g. specifying '\s+' as a separator. Not sure when you were playing last with pandas, but the c-parser has been in place since late 2012. (version 0.8.0)

Re: [Numpy-discussion] ANN: NumPy 1.7.2rc1 release

On 13.11.2013, at 3:07AM, Charles R Harris charlesr.har...@gmail.com wrote: Python 2.4 fixes at https://github.com/numpy/numpy/pull/4049. Thanks for the fixes; builds under OS X 10.5 now as well. There are two test errors (or maybe as nose problem?): NumPy version 1.7.2rc1 NumPy is installed

Re: [Numpy-discussion] ANN: NumPy 1.7.2rc1 release

Hi, On 03.11.2013, at 5:42PM, Julian Taylor jtaylor.deb...@googlemail.com wrote: I'm happy to announce the release candidate of Numpy 1.7.2. This is a bugfix only release supporting Python 2.4 - 2.7 and 3.1 - 3.3. on OS X 10.5, build and tests succeed for Python 2.5-3.3, but Python 2.4.4

Re: [Numpy-discussion] Removal of numarray and oldnumeric packages.

On 23.09.2013, at 7:03PM, Charles R Harris charlesr.har...@gmail.com wrote: I have gotten no feedback on the removal of the numarray and oldnumeric packages. Consequently the removal will take place on 9/28. Scream now or never... The only thing I'd care about is the nd_image subpackage,

Re: [Numpy-discussion] genfromtxt and gzip

On 05.06.2013, at 9:52AM, Ted To rainexpec...@theo.to wrote: From the list archives (2011), I noticed that there is a bug in the python gzip module that causes genfromtxt to fail with python 2 but this bug is not a problem for python 3. When I tried to use genfromtxt and python 3 with a

Re: [Numpy-discussion] printing array in tabular form

On 10.05.2013, at 1:20PM, Sudheer Joseph sudheer.jos...@yahoo.com wrote: If some one has a quick way I would like to learn from them or get a referecence where the formatting part is described which was my intention while posting here. As I have been using fortran I just tried to use it

Re: [Numpy-discussion] printing array in tabular form

On 10.05.2013, at 2:51PM, Daniele Nicolodi dani...@grinta.net wrote: If you wish to format numpy arrays preceding them with a variable name, the following is a possible solution that gives the same formatting as in your example: import numpy as np import sys def format(out, v, name):

Re: [Numpy-discussion] printing array in tabular form

Dear Sudheer, On 07.05.2013, at 11:14AM, Sudheer Joseph sudheer.jos...@yahoo.com wrote: I need to print few arrays in a tabular form for example below array IL has 25 elements, is there an easy way to print this as 5x5 comma separated table? in python IL=[] for i in

Re: [Numpy-discussion] Please stop bottom posting!!

On 12.04.2013, at 2:14AM, Charles R Harris charlesr.har...@gmail.com wrote: On Thu, Apr 11, 2013 at 5:49 PM, Colin J. Williams cjwilliam...@gmail.com wrote: On 11/04/2013 7:20 PM, Paul Hobson wrote: On Wed, Apr 3, 2013 at 4:28 PM, Doug Coleman doug.cole...@gmail.com wrote: Also, gmail

Re: [Numpy-discussion] Trouble building numpy on different version of OSX.

On 14.02.2013, at 3:55PM, Steve Spicklemire st...@spvi.com wrote: I got Xcode 4,6 from the App Store. I don't think it's the SDK since the python 2.7 version builds fine. It's just the 3.2 version that doesn't have the -I/Library/Frameworks/Python.Framework/Versions/3.2/include/python3.2m in

Re: [Numpy-discussion] how do I specify maximum line length when using savetxt?

On 06.12.2012, at 12:40AM, Mark Bakker wrote: I guess I wasn't explicit enough. Say I have an array with 100 numbers and I want to write it to a file with 6 numbers on each line (and hence, only 4 on the last line). Can I use savetxt to do that? What other easy tool does numpy have to do

Re: [Numpy-discussion] Simple Loadtxt question

On 29.11.2012, at 1:21AM, Robert Love wrote: I have a file with thousands of lines like this: Signal was returned in 204 microseconds Signal was returned in 184 microseconds Signal was returned in 199 microseconds Signal was returned in 4274 microseconds Signal was returned in 202

Re: [Numpy-discussion] Synonym standards

On 27.07.2012, at 3:27PM, Benjamin Root wrote: I would prefer not to use: from xxx import *, because of the name pollution. The name convention that I copied above facilitates avoiding the pollution. In the same spirit, I've used: import pylab as plb But in that same spirit,

Re: [Numpy-discussion] Synonym standards

On 27 Jul 2012, at 17:58, Tony Yu wrote: On Fri, Jul 27, 2012 at 11:39 AM, Derek Homeier de...@astro.physik.uni-goettingen.de wrote: On 27.07.2012, at 3:27PM, Benjamin Root wrote: I would prefer not to use: from xxx import *, because of the name pollution. The name

Re: [Numpy-discussion] Synonym standards

On 27.07.2012, at 8:30PM, Fernando Perez fperez@gmail.com wrote: On Fri, Jul 27, 2012 at 9:43 AM, Derek Homeier de...@astro.physik.uni-goettingen.de wrote: thanks, that was exactly what I was looking for - together with c.TerminalIPythonApp.exec_lines = ['import sys

Re: [Numpy-discussion] silly isscalar question

On 29 May 2012, at 15:00, Mark Bakker wrote: Why does isscalar('hello') return True? I thought it would check for a number? No, it checks for something that is of 'scalar type', which probably can be translated as 'not equivalent to an array'. Since strings can form numpy arrays, I guess

Re: [Numpy-discussion] silly isscalar question

On 29 May 2012, at 15:42, Nathaniel Smith wrote: I note the fine distinction between np.isscalar( ('hello') ) and np.isscalar( ('hello'), )... NB you mean np.isscalar( ('hello',) ), which creates a single-element tuple. A trailing comma attached to a value in Python normally creates a

Re: [Numpy-discussion] ANN: NumPy 1.6.2 release candidate 1

On 06.05.2012, at 8:16AM, Paul Anton Letnes wrote: All tests for 1.6.2rc1 pass on Mac OS X 10.7.3 python 2.7.2 gcc 4.2 (Apple) Passing as well on 10.6 x86_64 and on 10.5.8 ppc with python 2.5.6/2.6.6/2.7.2 Apple gcc 4.0.1, but I am getting one failure on Lion (same with Python

Re: [Numpy-discussion] how to check type of array?

On 29 Mar 2012, at 13:54, Chao YUE wrote: how can I check type of array in if condition expression? In [75]: type(a) Out[75]: type 'numpy.ndarray' In [76]: a.dtype Out[76]: dtype('int32') a.dtype=='int32'? this and a.dtype=='i4' a.dtype==np.int32 all work. For a more general check

Re: [Numpy-discussion] how to check type of array?

On 29 Mar 2012, at 14:49, Robert Kern wrote: all work. For a more general check (e.g. if it is any type of integer), you can do np.issubclass_(a.dtype.type, np.integer) I don't recommend using that. Use np.issubdtype(a.dtype, np.integer) instead. Sorry, you're right, this works the same

Re: [Numpy-discussion] How to Extract the Number of Rows and Columns in a Matrix

On 27.03.2012, at 1:26AM, Olivier Delalleau wrote: len(M) will give you the number of rows of M. For columns I just use M.shape[1] myself, I don't know if there exists a shortcut. You can use tuple unpacking, if that helps keeping your code conciser… nrow, ncol = M.shape Cheers,

Re: [Numpy-discussion] AttributeError with shape command

On 27.03.2012, at 2:07AM, Stephanie Cooke wrote: I am new to numpy. When I try to use the command array.shape, I get the following error: AttributeError: 'list' object has no attribute 'shape' Is anyone familiar with this type of error? It means 'array' actually is not one, more

Re: [Numpy-discussion] Trying to read 500M txt file using numpy.genfromtxt within ipython shell

On 20 Mar 2012, at 14:40, Chao YUE wrote: I would be in agree. thanks! I use gawk to separate the file into many files by year, then it would be easier to handle. anyway, it's not a good practice to produce such huge line txt files Indeed it's not, but it's also not good practice to

Re: [Numpy-discussion] remove redundant dimension in a ndarray?

Dear Chao, Do we have a function in numpy that can automatically shrink a ndarray with redundant dimension? like I have a ndarray with shape of (13,1,1,160,1), now I have written a small function to change the array to dimension of (13,160) [reduce the extra dimension with length as 1].

Re: [Numpy-discussion] Saving and loading a structured array from a TEXT file

On 23 Jan 2012, at 21:15, Emmanuel Mayssat wrote: Is there a way to save a structured array in a text file? My problem is not so much in the saving procedure, but rather in the 'reloading' procedure. See below In [3]: import numpy as np In [4]: r = np.ones(3,dtype=[('name', '|S5'),

Re: [Numpy-discussion] Saving and loading a structured array from a TEXT file

On 23 Jan 2012, at 22:07, Derek Homeier wrote: In [4]: r = np.ones(3,dtype=[('name', '|S5'), ('foo', 'i8'), ('bar', 'f8')]) In [5]: r.tofile('toto.txt',sep='\n') bash-4.2$ cat toto.txt ('1', 1, 1.0) ('1', 1, 1.0) ('1', 1, 1.0) cnv = {0: lambda s: s.lstrip('('), -1: lambda s

Re: [Numpy-discussion] 'Advanced' save and restore operation

On 24 Jan 2012, at 01:45, Olivier Delalleau wrote: Note sure if there's a better way, but you can do it with some custom load and save functions: with open('f.txt', 'w') as f: ... f.write(str(x.dtype) + '\n') ... numpy.savetxt(f, x) with open('f.txt') as f: ... dtype =

Re: [Numpy-discussion] find location of maximum values

On 04.01.2012, at 5:10AM, questions anon wrote: Thanks for your responses but I am still having difficuties with this problem. Using argmax gives me one very large value and I am not sure what it is. There shouldn't be any issues with the shape. The latitude and longitude are the same

Re: [Numpy-discussion] structured array with submember assign

On 26.12.2011, at 7:37PM, Fabian Dill wrote: I have a problem with a structured numpy array. I create is like this: tiles = numpy.zeros((header[width], header[height],3), dtype = numpy.uint8) and later on, assignments such as this: tiles[x, y,0] = 3 Now uint8 is not sufficient anymore,

Re: [Numpy-discussion] numpy1.6.1 install fortran compiler error

Hi Jack, In order to install scipy, I am trying to install numpy 1.6.1. on GNU/linux redhat 2.6.18. But, I got error about fortran compiler. I have gfortran. I do not have f77/f90/g77/g90. that's good! I run : python setup.py build --fcompiler=gfortran It woks well and tells

Re: [Numpy-discussion] numpy1.6.1 install fortran compiler error

On 20.12.2011, at 9:01PM, Jack Bryan wrote: customize Gnu95FCompiler using config C compiler: gcc -pthread -fno-strict-aliasing -g -O2 -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC compile options: '-Inumpy/core/src/private -Inumpy/core/src -Inumpy/core -Inumpy/core/src/npymath

Re: [Numpy-discussion] numpy 1.7.0 release?

On 06.12.2011, at 11:13PM, Wes McKinney wrote: This isn't the place for this discussion but we should start talking about building a *high performance* flat file loading solution with good column type inference and sensible defaults, etc. It's clear that loadtable is aiming for highest

Re: [Numpy-discussion] loop through values in a array and find maximum as looping

On 07.12.2011, at 5:07AM, Olivier Delalleau wrote: I *think* it may work better if you replace the last 3 lines in your loop by: a=all_TSFC[0] if len(all_TSFC) 1: N.maximum(a, TSFC, out=a) Not 100% sure that would work though, as I'm not entirely

Re: [Numpy-discussion] loop through values in a array and find maximum as looping

On 07.12.2011, at 5:54AM, questions anon wrote: sorry the 'all_TSFC' is for my other check of maximum using concatenate and N.max, I know that works so I am comparing it to this method. The only reason I need another method is for memory error issues. I like the code I have written so far

Re: [Numpy-discussion] upsample or scale an array

On 03.12.2011, at 6:22PM, Robin Kraft wrote: That does repeat the elements, but doesn't get them into the desired order. In [4]: print a [[1 2] [3 4]] In [7]: np.tile(a, 4) Out[7]: array([[1, 2, 1, 2, 1, 2, 1, 2], [3, 4, 3, 4, 3, 4, 3, 4]]) In [8]: np.tile(a,

Re: [Numpy-discussion] upsample or scale an array

On 03.12.2011, at 6:47PM, Olivier Delalleau wrote: Ah sorry, I hadn't read carefully enough what you were trying to achieve. I think the double repeat solution looks like your best option then. Considering that it is a lot shorter than fixing the tile() result, you are probably right (I've

Re: [Numpy-discussion] numpy.array() of mixed integers and strings can truncate data

On 1 Dec 2011, at 17:39, Charles R Harris wrote: On Thu, Dec 1, 2011 at 6:52 AM, Thouis (Ray) Jones tho...@gmail.com wrote: Is this expected behavior? np.array([-345,4,2,'ABC']) array(['-34', '4', '2', 'ABC'], dtype='|S3') Given that strings should be the result, this looks like a

Re: [Numpy-discussion] numpy.array() of mixed integers and strings can truncate data

On 1 Dec 2011, at 21:35, Chris Barker wrote: On 12/1/2011 9:15 AM, Derek Homeier wrote: np.array((2, 12,0.001+2j), dtype='|S8') array(['2', '12', '(0.001+2'], dtype='|S8') - notice the last value is only truncated because it had first been converted into a standard complex

Re: [Numpy-discussion] float128 / longdouble on PPC - is it broken?

Hi, On 25 Oct 2011, at 21:14, Pauli Virtanen wrote: 25.10.2011 20:29, Matthew Brett kirjoitti: [clip] In [7]: (res-1) / 2**32 Out[7]: 8589934591.98 In [8]: np.float((res-1) / 2**32) Out[8]: 4294967296.0 Looks like a bug in the C library installed on the machine, then. It's

Re: [Numpy-discussion] Printing individual array elements with at least 15 significant digits

On 15.10.2011, at 9:21PM, Hugo Gagnon wrote: I need to print individual elements of a float64 array to a text file. However in the file I only get 12 significant digits, the same as with: a = np.zeros(3) a.fill(1./3) print a[0] 0. len(str(a[0])) - 2 12 whereas

Re: [Numpy-discussion] Float128 integer comparison

On 15.10.2011, at 9:42PM, Aronne Merrelli wrote: On Sat, Oct 15, 2011 at 1:12 PM, Matthew Brett matthew.br...@gmail.com wrote: Hi, Continuing the exploration of float128 - can anyone explain this behavior? np.float64(9223372036854775808.0) == 9223372036854775808L True

Re: [Numpy-discussion] genfromtxt

Hi Nils, On 11 Oct 2011, at 16:34, Nils Wagner wrote: How do I use genfromtxt to read a file with the following lines 11 2.2592365264892578D+01 22 2.2592365264892578D+01 13 2.669845581055D+00

Re: [Numpy-discussion] Nice float - integer conversion?

On 11 Oct 2011, at 20:06, Matthew Brett wrote: Have I missed a fast way of doing nice float to integer conversion? By nice I mean, rounding to the nearest integer, converting NaN to 0, inf, -inf to the max and min of the integer range? The astype method and cast functions don't do what I

Re: [Numpy-discussion] Nice float - integer conversion?

On 11.10.2011, at 9:18PM, josef.p...@gmail.com wrote: In [42]: c = np.zeros(4, np.int16) In [43]: d = np.zeros(4, np.int32) In [44]: np.around([1.6,np.nan,np.inf,-np.inf], out=c) Out[44]: array([2, 0, 0, 0], dtype=int16) In [45]: np.around([1.6,np.nan,np.inf,-np.inf], out=d) Out[45]:

Re: [Numpy-discussion] what to use in buildbot config for numpy testing

script. Cheers, Derek -- Derek Homeier Centre de Recherche Astrophysique de Lyon ENS Lyon 46, Allée d'Italie 69364 Lyon Cedex 07, France

Re: [Numpy-discussion] load from text files Pull Request Review

. Cheers, Derek -- Derek Homeier Centre de Recherche Astrophysique de Lyon ENS Lyon 46, Allée d'Italie 69364 Lyon Cedex 07, France

Re: [Numpy-discussion] Efficient way to load a 1Gb file?

… Cheers, Derek -- Derek Homeier Centre de Recherche Astrophysique de Lyon ENS Lyon 46, Allée d'Italie 69364 Lyon Cedex 07, France +33

Re: [Numpy-discussion] load from text files Pull Request Review

genfromtxt?) Cheers, Derek -- Derek Homeier Centre de Recherche Astrophysique de Lyon ENS Lyon 46, Allée d'Italie 69364 Lyon Cedex 07, France

Re: [Numpy-discussion] load from text files Pull Request Review

-- so you don't need to de-compress twice. Absolutely; on compressed data the time for the extra pass jumps up to +30-50%. Cheers, Derek -- Derek Homeier Centre de

Re: [Numpy-discussion] load from text files Pull Request Review

-- Derek Homeier Centre de Recherche Astrophysique de Lyon ENS Lyon 46, Allée d'Italie 69364 Lyon Cedex 07, France +33 1133 47272-8894

Re: [Numpy-discussion] saving groups of numpy arrays to disk

On 25.08.2011, at 8:42PM, Chris.Barker wrote: On 8/24/11 9:22 AM, Anthony Scopatz wrote: You can use Python pickling, if you do *not* have a requirement for: I can't recall why, but it seem pickling of numpy arrays has been fragile and not very performant. Hmm, the pure Python version

[Numpy-discussion] array_equal and array_equiv comparison functions for structured arrays

Hi, as the subject says, the array_* comparison functions currently do not operate on structured/record arrays. Pull request https://github.com/numpy/numpy/pull/146 implements these comparisons. There are two commits, differing in their interpretation whether two arrays with different field

Re: [Numpy-discussion] Trim a numpy array in numpy.

Hi Hongchun, On 16 Aug 2011, at 23:19, Hongchun Jin wrote: I have a question regarding how to trim a string array in numpy. import numpy as np x = np.array(['aaa.hdf', 'bbb.hdf', 'ccc.hdf', 'ddd.hdf']) I expect to trim a certain part of each element in the array, for example '.hdf',

Re: [Numpy-discussion] Trim a numpy array in numpy.

On 16 Aug 2011, at 23:51, Hongchun Jin wrote: Thanks Derek for the quick reply. But I am sorry, I did not make it clear in my last email. Assume I have an array like ['CAL_LID_L2_05kmCLay-Prov-V3-01.2008-01-01T00-37-48ZD.hdf' 'CAL_LID_L2_05kmCLay-Prov-V3-01.2008-01-01T00-37-48ZD.hdf'

Re: [Numpy-discussion] Efficient way to load a 1Gb file?

On 10 Aug 2011, at 19:22, Russell E. Owen wrote: A coworker is trying to load a 1Gb text data file into a numpy array using numpy.loadtxt, but he says it is using up all of his machine's 6Gb of RAM. Is there a more efficient way to read such text data files? The npyio routines (loadtxt as

Re: [Numpy-discussion] Efficient way to load a 1Gb file?

On 10 Aug 2011, at 22:03, Gael Varoquaux wrote: On Wed, Aug 10, 2011 at 04:01:37PM -0400, Anne Archibald wrote: A 1 Gb text file is a miserable object anyway, so it might be desirable to convert to (say) HDF5 and then throw away the text file. +1 There might be concerns about ensuring data

Re: [Numpy-discussion] [ANN] Cython 0.15

On 7 Aug 2011, at 04:09, Sturla Molden wrote: Den 06.08.2011 11:18, skrev Dag Sverre Seljebotn: We are excited to announce the release of Cython 0.15, which is a huge step forward in achieving full Python language coverage as well as many new features, optimizations, and bugfixes. This

Re: [Numpy-discussion] [ANN] Cython 0.15

On 7 Aug 2011, at 22:31, Paul Anton Letnes wrote: Looks like you have done some great work! I've been using f2py in the past, but I always liked the idea of cython - gradually wrapping more and more code as the need arises. I read somewhere that fortran wrapping with cython was coming -

Re: [Numpy-discussion] [ANN] Cython 0.15

On 7 Aug 2011, at 23:27, Dag Sverre Seljebotn wrote: Enumpy_test.c: In function ‘PyInit_numpy_test’: numpy_test.c:11611: warning: ‘return’ with no value, in function returning non-void .numpy_test.cpp: In function ‘PyObject* PyInit_numpy_test()’: numpy_test.cpp:11611: error:

[Numpy-discussion] longlong format error with Python = 2.6 in scalartypes.c

Hi, commits c15a807e and c135371e (thus most immediately addressed to Mark, but I am sending this to the list hoping for more insight on the issue) introduce a test failure with Python 2.5+2.6 on Mac: FAIL: test_timedelta_scalar_construction (test_datetime.TestDateTime)

Re: [Numpy-discussion] Segmentation Fault in Numpy.test()

On 2 Aug 2011, at 18:57, Thomas Markovich wrote: It appears that uninstalling python 2.7 and installing the scipy superpack with the apple standard python removes the Did the superpack installer automatically install numpy to the python2.7 directory when present? Even if so, I reckon you

Re: [Numpy-discussion] Finding many ways to incorrectly create a numpy array. Please advice

On 2 Aug 2011, at 19:15, Christopher Barker wrote: In [32]: s = numpy.array(a, dtype=tfc_dtype) --- TypeError Traceback (most recent call last) /Users/cbarker/ipython console in

Re: [Numpy-discussion] Can I index array starting with 1?

On 29.07.2011, at 1:19AM, Stéfan van der Walt wrote: On Thu, Jul 28, 2011 at 4:10 PM, Anne Archibald aarch...@physics.mcgill.ca wrote: Don't forget the everything-looks-like-a-nail approach: make all your arrays one bigger than you need and ignore element zero. Hehe, why didn't I think of

Re: [Numpy-discussion] Can I index array starting with 1?

On 29.07.2011, at 1:38AM, Anne Archibald wrote: The can is open and the worms are everywhere, so: The big problem with one-based indexing for numpy is interpretation. In python indexing, -1 is the last element of the array, and ranges have a specific meaning. In a hypothetical one-based

Re: [Numpy-discussion] ANN: NumPy 1.6.1 release candidate 2

On 07.07.2011, at 7:16PM, Robert Pyle wrote: .../Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/core/numeric.py:1922: RuntimeWarning: invalid value encountered in absolute return all(less_equal(absolute(x-y), atol + rtol * absolute(y)))

Re: [Numpy-discussion] broacasting question

On 30.06.2011, at 7:32PM, Thomas K Gamble wrote: I'm trying to convert some IDL code to python/numpy and i'm having some trouble understanding the rules for boradcasting during some operations. example: given the following arrays: a = array((2048,3577), dtype=float) b =

Re: [Numpy-discussion] broacasting question

On 30.06.2011, at 11:57PM, Thomas K Gamble wrote: np.add(b.reshape(2048,3136) * c, d, out=a[:,:3136]) But to say whether this is really the equivalent result to what IDL does, one would have to study the IDL manual in detail or directly compare the output (e.g. check what happens to the

Re: [Numpy-discussion] fast numpy i/o

On 27.06.2011, at 6:36PM, Robert Kern wrote: Some late comments on the note (I was a bit surprised that HDF5 installation seems to be a serious hurdle to many - maybe I've just been profiting from the fink build system for OS X here - but I also was not aware that the current netCDF is

Re: [Numpy-discussion] fast numpy i/o

On 21.06.2011, at 7:58PM, Neal Becker wrote: I think, in addition, that hdf5 is the only one that easily interoperates with matlab? speaking of hdf5, I see: pyhdf5io 0.7 - Python module containing high-level hdf5 load and save functions. h5py 2.0.0 - Read and write HDF5 files from

Re: [Numpy-discussion] npyio - gzip 271 Error -3 while decompressing ?

Moin Denis, On 20 Jun 2011, at 19:04, denis wrote: a separate question, have you run genfromtxt( xx.csv.gz ) lately ? I haven't, and I was not particularly involved with it before this patch, so this would possibly be better addressed to the list. On on

Re: [Numpy-discussion] loadtxt ndmin option

On 31 May 2011, at 21:28, Pierre GM wrote: On May 31, 2011, at 6:37 PM, Derek Homeier wrote: On 31 May 2011, at 18:25, Pierre GM wrote: On May 31, 2011, at 5:52 PM, Derek Homeier wrote: I think stuff like multiple delimiters should have been dealt with before, as the right place to insert

Re: [Numpy-discussion] ANN: Numpy 1.6.1 release candidate 1

Hi Ralf, On 19 Jun 2011, at 12:28, Ralf Gommers wrote: numpy.test('full') Running unit tests for numpy NumPy version 1.6.1rc1 NumPy is installed in /sw/lib/python3.2/site-packages/numpy Python version 3.2 (r32:88445, Mar 1 2011, 18:28:16) [GCC 4.0.1 (Apple Inc. build 5493)] nose

Re: [Numpy-discussion] genfromtxt converter question

On 18 Jun 2011, at 04:48, gary ruben wrote: Thanks guys - I'm happy with the solution for now. FYI, Derek's suggestion doesn't work in numpy 1.5.1 either. For any developers following this thread, I think this might be a nice use case for genfromtxt to handle in future. Numpy 1.6.0 and above

[Numpy-discussion] Enhancements and bug fix for npyio

Hi, in my experience numbers loaded from text files very often require identical conversion for all data (e.g. parsing Fortran-style double precision, or German vs. English decimals...). Yet loadtxt and genfromtxt in such cases require the user to construct a dictionary of converters for

Re: [Numpy-discussion] code review/build test for datetime business day API

On 17.06.2011, at 8:05PM, Mark Wiebe wrote: On Thu, Jun 16, 2011 at 8:18 PM, Derek Homeier de...@astro.physik.uni-goettingen.de wrote: On 17.06.2011, at 2:02AM, Mark Wiebe wrote: ok, that was a lengthy hunt, but it's in printing the string in make_iso_8601_date: tmplen

Re: [Numpy-discussion] genfromtxt converter question

Hi Gary, On 17.06.2011, at 5:39PM, gary ruben wrote: Thanks for the hints Olivier and Bruce. Based on them, the following is a working solution, although I still have that itchy sense that genfromtxt should be able to do it directly. import numpy as np from StringIO import StringIO a =

Re: [Numpy-discussion] genfromtxt converter question

On 17.06.2011, at 11:01PM, Olivier Delalleau wrote: You were just overdoing it by already creating an array with the converter, this apparently caused genfromtxt to create a structured array from the input (which could be converted back to an ndarray, but that can prove tricky as well) -

Re: [Numpy-discussion] code review/build test for datetime business day API

Hi Mark, On 16.06.2011, at 5:40PM, Mark Wiebe wrote: np.datetime64('2011-06-16 02:03:04Z', 'D') np.datetime64('-06-16','D') I've tried to track this down in datetime.c, but unsuccessfully so (i.e. I could not connect it to any of the dts-year assignments therein). This is

Re: [Numpy-discussion] code review/build test for datetime business day API

On 17.06.2011, at 2:02AM, Mark Wiebe wrote: ok, that was a lengthy hunt, but it's in printing the string in make_iso_8601_date: tmplen = snprintf(substr, sublen, %04 NPY_INT64_FMT, dts-year); fprintf(stderr, printed %d[%d]: dts-year=%lld: %s\n, tmplen, sublen, dts-year, substr);

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