Re: [Numpy-discussion] migration of all scipy.org mailing lists

Ralf Gommers wrote: > On Thu, Mar 23, 2017 at 12:18 AM, Neal Becker <ndbeck...@gmail.com> wrote: > >> Has anyone taken care of notifying gmane about this? >> > > We will have to update this info in quite a few places after the move is > done. Including Gman

Re: [Numpy-discussion] migration of all scipy.org mailing lists

Has anyone taken care of notifying gmane about this? Ralf Gommers wrote: > Hi all, > > The server for the scipy.org mailing list is in very bad shape, so we (led > by Didrik Pinte) are planning to complete the migration of active mailing > lists to the python.org infrastructure and to

Re: [Numpy-discussion] NumPy 1.12.0 release

Matthew Brett wrote: > On Tue, Jan 17, 2017 at 3:47 PM, Neal Becker <ndbeck...@gmail.com> wrote: >> Matthew Brett wrote: >> >>> Hi, >>> >>> On Tue, Jan 17, 2017 at 5:56 AM, Neal Becker <ndbeck...@gmail.com> >>> wrote: >>

Re: [Numpy-discussion] [SciPy-Dev] NumPy 1.12.0 release

Nathaniel Smith wrote: > On Tue, Jan 17, 2017 at 3:47 PM, Neal Becker <ndbeck...@gmail.com> wrote: >> Matthew Brett wrote: >> >>> Hi, >>> >>> On Tue, Jan 17, 2017 at 5:56 AM, Neal Becker <ndbeck...@gmail.com> >>> wrote: >>

Re: [Numpy-discussion] NumPy 1.12.0 release

Charles R Harris wrote: > Hi All, > > I'm pleased to announce the NumPy 1.12.0 release. This release supports > Python 2.7 and 3.4-3.6. Wheels for all supported Python versions may be > downloaded from PiPY > , the tarball > and zip files

Re: [Numpy-discussion] array comprehension

Francesc Alted wrote: > 2016-11-04 14:36 GMT+01:00 Neal Becker <ndbeck...@gmail.com>: > >> Francesc Alted wrote: >> >> > 2016-11-04 13:06 GMT+01:00 Neal Becker <ndbeck...@gmail.com>: >> > >> >> I find I often write: >> >&

Re: [Numpy-discussion] array comprehension

Francesc Alted wrote: > 2016-11-04 13:06 GMT+01:00 Neal Becker <ndbeck...@gmail.com>: > >> I find I often write: >> np.array ([some list comprehension]) >> >> mainly because list comprehensions are just so sweet. >> >> But I imagine this isn

[Numpy-discussion] array comprehension

I find I often write: np.array ([some list comprehension]) mainly because list comprehensions are just so sweet. But I imagine this isn't particularly efficient. I wonder if numpy has a "better" way, and if not, maybe it would be a nice addition?

Re: [Numpy-discussion] update on mailing list issues

Ralf Gommers wrote: > Hi all, > > We've had a number of issues with the reliability of the mailman setup > that powers the mailing lists for NumPy, SciPy and several other projects. > To address that we'll start migrating to the python.org provided > infrastructure, which should be much more

Re: [Numpy-discussion] State-of-the-art to use a C/C++ library from Python

Jason Newton wrote: > I just wanted to follow up on the C++ side of OP email - Cython has quite > a > few difficulties working with C++ code at the moment. It's really more of > a C solution most of the time and you must split things up into a mostly C > call interface (that is the C code Cython

Re: [Numpy-discussion] State-of-the-art to use a C/C++ library from Python

Michael Bieri wrote: > Hi all > > There are several ways on how to use C/C++ code from Python with NumPy, as > given in http://docs.scipy.org/doc/numpy/user/c-info.html . Furthermore, > there's at least pybind11. > > I'm not quite sure which approach is state-of-the-art as of 2016. How > would

Re: [Numpy-discussion] mtrand.c update 1.11 breaks my crappy code

Nathaniel Smith wrote: > On Apr 6, 2016 06:31, "Robert Kern" <robert.k...@gmail.com> wrote: >> >> On Wed, Apr 6, 2016 at 2:18 PM, Neal Becker <ndbeck...@gmail.com> wrote: >> > >> > I have C++ code that tries to share the mtrand state. It

Re: [Numpy-discussion] mtrand.c update 1.11 breaks my crappy code

Neal Becker wrote: > Robert Kern wrote: > >> On Wed, Apr 6, 2016 at 2:18 PM, Neal Becker <ndbeck...@gmail.com> wrote: >>> >>> I have C++ code that tries to share the mtrand state. It unfortunately >>> depends on the layout of

Re: [Numpy-discussion] mtrand.c update 1.11 breaks my crappy code

Robert Kern wrote: > On Wed, Apr 6, 2016 at 2:18 PM, Neal Becker <ndbeck...@gmail.com> wrote: >> >> I have C++ code that tries to share the mtrand state. It unfortunately >> depends on the layout of RandomState which used to be: >> >> struct __pyx_obj_6

[Numpy-discussion] mtrand.c update 1.11 breaks my crappy code

I have C++ code that tries to share the mtrand state. It unfortunately depends on the layout of RandomState which used to be: struct __pyx_obj_6mtrand_RandomState { PyObject_HEAD rk_state *internal_state; PyObject *lock; }; But with 1.11 it's: struct __pyx_obj_6mtrand_RandomState {

[Numpy-discussion] tracemalloc + numpy?

I'm trying tracemalloc to find memory usage. Will numpy array memory usage be counted by tracemalloc? (Doesn't seem to) ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org https://mail.scipy.org/mailman/listinfo/numpy-discussion

[Numpy-discussion] julia - Multidimensional algorithms and iteration

http://julialang.org/blog/2016/02/iteration/ ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org https://mail.scipy.org/mailman/listinfo/numpy-discussion

[Numpy-discussion] what would you expect A[none] to do?

In my case, what it does is: A.shape = (5760,) A[none] -> (1, 5760) In my case, use of none here is just a mistake. But why would you want this to be accepted at all, and how should it be interpreted? ___ NumPy-Discussion mailing list

Re: [Numpy-discussion] what would you expect A[none] to do?

Neal Becker wrote: > In my case, what it does is: > > A.shape = (5760,) > A[none] -> (1, 5760) > > In my case, use of none here is just a mistake. But why would you want > this to be accepted at all, and how should it be interpreted? Actually, in my particular case, if

[Numpy-discussion] reshaping array question

I have an array of shape (7, 24, 2, 1024) I'd like an array of (7, 24, 2048) such that the elements on the last dimension are interleaving the elements from the 3rd dimension [0,0,0,0] -> [0,0,0] [0,0,1,0] -> [0,0,1] [0,0,0,1] -> [0,0,2] [0,0,1,1] -> [0,0,3] ... What might be the simplest way

Re: [Numpy-discussion] reshaping array question

Robert Kern wrote: > On Tue, Nov 17, 2015 at 3:48 PM, Neal Becker <ndbeck...@gmail.com> wrote: >> >> I have an array of shape >> (7, 24, 2, 1024) >> >> I'd like an array of >> (7, 24, 2048) >> >> such that the elements on the last dimensio

Re: [Numpy-discussion] Numpy 1.10.0 release

lots of warning with openblas python setup.py build Running from numpy source directory. /usr/lib64/python2.7/distutils/dist.py:267: UserWarning: Unknown distribution option: 'test_suite' warnings.warn(msg) blas_opt_info: blas_mkl_info: libraries mkl,vml,guide not found in

Re: [Numpy-discussion] Numpy 1.10.0 release

1 test failure: FAIL: test_blasdot.test_blasdot_used -- Traceback (most recent call last): File "/usr/lib/python2.7/site-packages/nose/case.py", line 197, in runTest self.test(*self.arg) File

Re: [Numpy-discussion] Numpy 1.10.0 release

Sebastian Berg wrote: > On Di, 2015-10-06 at 07:53 -0400, Neal Becker wrote: >> 1 test failure: >> >> FAIL: test_blasdot.test_blasdot_used >> -- >> Traceback (most recent call last): >>

Re: [Numpy-discussion] Defining a white noise process using numpy

Daniel Bliss wrote: Hi all, Can anyone give me some advice for translating this equation into code using numpy? eta(t) = lim(dt - 0) N(0, 1/sqrt(dt)), where N(a, b) is a Gaussian random variable of mean a and variance b**2. This is a heuristic definition of a white noise process.

[Numpy-discussion] strange casting rules

np.uint64(-1)+0 Out[36]: 1.8446744073709552e+19 I often work on signal processing requiring bit-exact integral arithmetic. Promoting to float is not helpful - I don't understand the logic of the above example. ___ NumPy-Discussion mailing list

[Numpy-discussion] stats functions with weight support

The histogram function supports a weights option, but most others (e.g., percentile) do not. For my problem, I have a trace of the amounts of time (floating point) that my machine under test is in each of N states. I'd like to produce histograms, kde, maybe nice pics with seaborn. I can use

[Numpy-discussion] not inheriting from ndarray

I wanted the function of an array that accumulates my results, it starts at zero size, and resizes as needed. New results are added using accumulated += new_array A simple implementation of this is here: https://gist.github.com/2ab48e25fd460990d045.git I have 2 questions: 1. Is this a

Re: [Numpy-discussion] not inheriting from ndarray

Neal Becker wrote: I wanted the function of an array that accumulates my results, it starts at zero size, and resizes as needed. New results are added using accumulated += new_array A simple implementation of this is here: https://gist.github.com/2ab48e25fd460990d045.git I have 2

[Numpy-discussion] dimension independent copy of corner of array

I want to copy an array to the corner of a new array. What is a dimension independent way to say: newarr[:i0,:i1,...] = oldarray where (i0,i1...) is oldarray.shape? ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org

Re: [Numpy-discussion] dimension independent copy of corner of array

Robert Kern wrote: newarr[tuple(slice(0, i) for i in oldarray.shape)] = oldarray On Mon, Jul 13, 2015 at 12:34 PM, Neal Becker ndbeck...@gmail.com wrote: I want to copy an array to the corner of a new array. What is a dimension independent way to say: newarr[:i0,:i1,...] = oldarray

Re: [Numpy-discussion] floats for indexing, reshape - too strict ?

josef.p...@gmail.com wrote: On Wed, Jul 1, 2015 at 10:32 AM, Sebastian Berg sebast...@sipsolutions.net wrote: On Mi, 2015-07-01 at 10:05 -0400, josef.p...@gmail.com wrote: About the deprecation warning for using another type than integers, in ones, reshape, indexing and so on:

[Numpy-discussion] python is cool

In order to make sure all my random number generators have good independence, it is a good practice to use a single shared instance (because it is already known to have good properties). A less-desirable alternative is to used rng's seeded with different starting states - in this case the

Re: [Numpy-discussion] python is cool

Roland Schulz wrote: Hi, I think the best way to solve this issue to not use a state at all. It is fast, reproducible even in parallel (if wanted), and doesn't suffer from the shared issue. Would be nice if numpy provided such a stateless RNG as implemented in Random123:

[Numpy-discussion] random.RandomState and deepcopy

It is common that to guarantee good statistical independence between various random generators, a singleton instance of an RNG is shared between them. So I typically have various random generator objects, which (sometimes several levels objects deep) embed an instance of RandomState. Now I

Re: [Numpy-discussion] random.RandomState and deepcopy

Robert Kern wrote: On Fri, Mar 13, 2015 at 5:34 PM, Neal Becker ndbeck...@gmail.com wrote: It is common that to guarantee good statistical independence between various random generators, a singleton instance of an RNG is shared between them. So I typically have various random generator

Re: [Numpy-discussion] Introductory mail and GSoc Project Vector math library integration

Ralf Gommers wrote: On Wed, Mar 11, 2015 at 11:20 PM, Dp Docs sdpa...@gmail.com wrote: On Thu, Mar 12, 2015 at 2:01 AM, Daπid davidmen...@gmail.com wrote: On 11 March 2015 at 16:51, Dp Docs sdpa...@gmail.com wrote: On Wed, Mar 11, 2015 at 7:52 PM, Sturla Molden

[Numpy-discussion] unpacking data values into array of bits

I need to transmit some data values. These values will be float and long values. I need them encoded into a string of bits. The only way I found so far to do this seems rather roundabout: np.unpackbits (np.array (memoryview(struct.pack ('d', pi Out[45]: array([0, 0, 0, 1, 1, 0, 0, 0, 0,

Re: [Numpy-discussion] unpacking data values into array of bits

Robert Kern wrote: On Thu, Feb 12, 2015 at 2:21 PM, Neal Becker ndbeck...@gmail.com wrote: I need to transmit some data values. These values will be float and long values. I need them encoded into a string of bits. The only way I found so far to do this seems rather roundabout

Re: [Numpy-discussion] unpacking data values into array of bits

Robert Kern wrote: On Thu, Feb 12, 2015 at 3:22 PM, Neal Becker ndbeck...@gmail.com wrote: Robert Kern wrote: On Thu, Feb 12, 2015 at 3:00 PM, Neal Becker ndbeck...@gmail.com wrote: Robert Kern wrote: On Thu, Feb 12, 2015 at 2:21 PM, Neal Becker ndbeck...@gmail.com wrote

Re: [Numpy-discussion] Views of a different dtype

I find it useful to be able to view a simple 1D contiguous array of complex as float (alternative real and imag), and also the do the reverse. ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org

[Numpy-discussion] question np.partition

It sounds like np.partition could be used to answer the question: give me the highest K elements in a vector. Is this a correct interpretation? Something like partial sort, but returned elements are unsorted. I could really make some use of this, but in my case it is a list of objects I need

[Numpy-discussion] simple reduction question

What would be the most efficient way to compute: c[j] = \sum_i (a[i] * b[i,j]) where a[i] is a 1-d vector, b[i,j] is a 2-d array? This seems to be one way: import numpy as np a = np.arange (3) b = np.arange (12).reshape (3,4) c = np.dot (a, b).sum() but np.dot returns a vector, which then

Re: [Numpy-discussion] simple reduction question

Nathaniel Smith wrote: On Wed, Dec 24, 2014 at 3:25 PM, Neal Becker ndbeck...@gmail.com wrote: What would be the most efficient way to compute: c[j] = \sum_i (a[i] * b[i,j]) where a[i] is a 1-d vector, b[i,j] is a 2-d array? I think this formula is just np.dot(a, b). Did you mean c

[Numpy-discussion] multi-dimensional c++ proposal

The multi-dimensional c++ stuff is interesting (about time!) http://www.open-std.org/JTC1/SC22/WG21/docs/papers/2014/n3851.pdf -- -- Those who don't understand recursion are doomed to repeat it ___ NumPy-Discussion mailing list

[Numpy-discussion] array indexing question

I'm using np.nonzero to construct the tuple: (array([0, 0, 0, 0, 1, 1, 1, 1, 2, 2, 2, 2]), array([1, 3, 5, 7, 2, 3, 6, 7, 4, 5, 6, 7])) Now what I want is the 2-D index array: [1,3,5,7, 2,3,6,7, 4,5,6,7] Any ideas? -- -- Those who don't understand recursion are doomed to repeat it

[Numpy-discussion] why does u.resize return None?

It would be useful if u.resize returned the new array, so it could be used for chaining operations -- -- Those who don't understand recursion are doomed to repeat it ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org

Re: [Numpy-discussion] why does u.resize return None?

https://github.com/numpy/numpy/issues/5064 Eelco Hoogendoorn wrote: agreed; I never saw the logic in returning none either. On Thu, Sep 11, 2014 at 4:27 PM, Neal Becker ndbeck...@gmail.com wrote: It would be useful if u.resize returned the new array, so it could be used for chaining

Re: [Numpy-discussion] SFMT (faster mersenne twister)

Robert Kern wrote: On Thu, Sep 4, 2014 at 12:32 PM, Neal Becker ndbeck...@gmail.com wrote: http://www.math.sci.hiroshima-u.ac.jp/~%20m-mat/MT/SFMT/index.html What would you like to say about it? If it is faster (and at least as good), maybe we'd like to adopt it to replace that used

Re: [Numpy-discussion] SFMT (faster mersenne twister)

Robert Kern wrote: On Fri, Sep 5, 2014 at 12:05 PM, Neal Becker ndbeck...@gmail.com wrote: Robert Kern wrote: On Thu, Sep 4, 2014 at 12:32 PM, Neal Becker ndbeck...@gmail.com wrote: http://www.math.sci.hiroshima-u.ac.jp/~%20m-mat/MT/SFMT/index.html What would you like to say about

[Numpy-discussion] SFMT (faster mersenne twister)

http://www.math.sci.hiroshima-u.ac.jp/~%20m-mat/MT/SFMT/index.html -- -- Those who don't understand recursion are doomed to repeat it ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion

Re: [Numpy-discussion] ANN: NumPy 1.9.0 release candidate 1 available

How do I run tests? python setup.py --help-commands claims 'test' is a command, but doesn't seem to work: python setup.py test Running from numpy source directory. /usr/lib64/python2.7/distutils/dist.py:267: UserWarning: Unknown distribution option: 'test_suite' warnings.warn(msg) usage:

Re: [Numpy-discussion] ANN: NumPy 1.9.0 release candidate 1 available

OK, it's fixed by doing: rm -rf ~/.local/lib/python2.7/site-packages/numpy* python setup.py install --user I guess something was not cleaned out from previous packages ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org

Re: [Numpy-discussion] fftw supported?

Sebastian Berg wrote: On Mo, 2014-06-02 at 07:27 -0400, Neal Becker wrote: I just d/l numpy-1.8.1 and try to build. I uncomment: [fftw] libraries = fftw3 This is fedora 20. fftw3 (and devel) is installed as fftw. I see nothing written to stderr during the build that has any

Re: [Numpy-discussion] ANN: Pandas 0.14.0 released

pip install --user --up pandas Downloading/unpacking pandas from https://pypi.python.org/packages/source/p/pandas/pandas-0.14.0.tar.gz#md5=b775987c0ceebcc8d5ace4a1241c967a ... Downloading/unpacking numpy=1.6.1 from

Re: [Numpy-discussion] Inverse function of numpy.polyval()

Yuxiang Wang wrote: Dear all, I was wondering is there a convenient inverse function of np.polyval(), where I give the y value and it solves for x? I know one way I could do this is: import numpy as np # Set up the question p = np.array([1, 1, -10]) y = 100 # Solve p_temp = p

[Numpy-discussion] Use of PyViennaCL on multi-core?

Typically, I have multiple CPU cores running in 'trivial parallel' mode - each running an independent point of a monte-carlo simulation. Could multiple processes multiplex use of a single GPU, using PyViennaCL? ___ NumPy-Discussion mailing list

[Numpy-discussion] incremental histogram

I needed a histogram that is built incrementally. My need is for 1D only. The idea is to not require storage of all the data (assume it could be too large). This is a naive implementation, perhaps someone could suggest something better. ,[ /home/nbecker/sigproc.ndarray/histogram3.py ] |

[Numpy-discussion] should rint return int?

I notice rint returns float. Shouldn't it return int? Would be useful when float is no longer acceptable as an index. I think conversion to an index using rint is a common idiom. ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org

Re: [Numpy-discussion] should rint return int?

Robert Kern wrote: On Mon, Apr 28, 2014 at 6:36 PM, Neal Becker ndbeck...@gmail.com wrote: I notice rint returns float. Shouldn't it return int? Would be useful when float is no longer acceptable as an index. I think conversion to an index using rint is a common idiom. C's rint() does

Re: [Numpy-discussion] numerical gradient, Jacobian, and Hessian

alex wrote: On Mon, Apr 21, 2014 at 3:13 AM, Eelco Hoogendoorn hoogendoorn.ee...@gmail.com wrote: As far as I can tell, [Theano] is actually the only tensor/ndarray aware differentiator out there And AlgoPy, a tensor/ndarray aware arbitrary order automatic differentiator

[Numpy-discussion] mtrand normal sigma = 0 too restrictive

Traceback (most recent call last): File ./test_inroute_frame.py, line 1694, in module run_line (sys.argv) File ./test_inroute_frame.py, line 1690, in run_line return run (opt, cmdline) File ./test_inroute_frame.py, line 1115, in run burst.tr (xbits,

Re: [Numpy-discussion] How security holes happen

Todd toddr...@gmail.com Wrote in message: ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion use modern programming languages with well designed exception handling --

[Numpy-discussion] FYI: libflatarray

I thought this was interesting: http://www.libgeodecomp.org/libflatarray.html ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion

[Numpy-discussion] another interesting high performance vector lib (yeppp)

http://www.yeppp.info/ ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion

Re: [Numpy-discussion] adding fused multiply and add to numpy

Charles R Harris wrote: On Wed, Jan 8, 2014 at 2:39 PM, Julian Taylor jtaylor.deb...@googlemail.com wrote: ... Another function that could be useful is a |a|**2 function, abs2 perhaps. Chuck I use mag_sqr all the time. It should be much faster for complex, if computed via: x.real**2

[Numpy-discussion] an indexing question

I have a 1d vector d. I want compute the means of subsets of this vector. The subsets are selected by looking at another vector s or same shape as d. This can be done as: [np.mean (d[s == i]) for i in range (size)] But I think this could be done directly with numpy addressing, without

Re: [Numpy-discussion] proposal: min, max of complex should give warning

Cera, Tim wrote: I don't work with complex numbers, but just sampling what others do: Python: no ordering, results in TypeError Matlab: sorts by magnitude http://www.mathworks.com/help/matlab/ref/sort.html R: sorts first by real, then by imaginary

Re: [Numpy-discussion] proposal: min, max of complex should give warning

Ralf Gommers wrote: On Tue, Dec 31, 2013 at 4:52 PM, Neal Becker ndbeck...@gmail.com wrote: Cera, Tim wrote: I don't work with complex numbers, but just sampling what others do: Python: no ordering, results in TypeError Matlab: sorts by magnitude http://www.mathworks.com/help

[Numpy-discussion] proposal: min, max of complex should give warning

I propose the following change: min, max applied to complex should give a warning. The rationale is, when the user applies min or max to complex, it's probably a mistake. ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org

[Numpy-discussion] nasty bug in 1.8.0??

This is np 1.8.0 on fedora x86_64: In [5]: x =np.array ((1,)) In [6]: x.shape Out[6]: (1,) In [7]: x.strides Out[7]: (9223372036854775807,) ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org

Re: [Numpy-discussion] nasty bug in 1.8.0??

I built using: CFLAGS='-march=native -O3' NPY_RELAXED_STRIDES_CHECKING=1 python3 setup.py install --user aπid wrote: I get: In [4]: x.strides Out[4]: (8,) Same architecture and OS, Numpy installed via Pip on Python 2.7.5. On 2 December 2013 20:08, Neal Becker ndbeck...@gmail.com

Re: [Numpy-discussion] nasty bug in 1.8.0??

I don't think that behavior is acceptable. Frédéric Bastien wrote: It is the NPY_RELAXED_STRIDES_CHECKING=1 flag that caused this. Fred On Mon, Dec 2, 2013 at 2:18 PM, Neal Becker ndbeck...@gmail.com wrote: I built using: CFLAGS='-march=native -O3' NPY_RELAXED_STRIDES_CHECKING=1

Re: [Numpy-discussion] nasty bug in 1.8.0??

:35 PM, Neal Becker ndbeck...@gmail.com wrote: I don't think that behavior is acceptable. Frédéric Bastien wrote: It is the NPY_RELAXED_STRIDES_CHECKING=1 flag that caused this. Fred On Mon, Dec 2, 2013 at 2:18 PM, Neal Becker ndbeck...@gmail.com wrote: I built using: CFLAGS='-march

Re: [Numpy-discussion] nasty bug in 1.8.0??

Jim Bosch wrote: If your arrays are contiguous, you don't really need the strides (use the itemsize instead). How is ndarray broken by this? ndarray is broken by this change because it expects the stride to be a multiple of the itemsize (I think; I'm just looking at code here, as I haven't

[Numpy-discussion] numpy.savetxt to string?

According to doc, savetxt only allows a file name. I'm surprised it doesn't allow a file-like object. How can I format text into a string? I would like savetxt to accept StringIO for this. ___ NumPy-Discussion mailing list

Re: [Numpy-discussion] strange behavior of += with object array

Robert Kern wrote: On Thu, Oct 31, 2013 at 11:22 PM, Neal Becker ndbeck...@gmail.com wrote: import numpy as np #from accumulator import stat2nd_double ## Just to make this really clear, I'm making a dummy ## class here that overloads += class stat2nd_double (object): def __iadd__

Re: [Numpy-discussion] strange behavior of += with object array

Robert Kern wrote: On Thu, Oct 31, 2013 at 11:22 PM, Neal Becker ndbeck...@gmail.com wrote: import numpy as np #from accumulator import stat2nd_double ## Just to make this really clear, I'm making a dummy ## class here that overloads += class stat2nd_double (object): def __iadd__

Re: [Numpy-discussion] ANN: NumPy 1.8.0 release.

Thanks for the release! I am having a hard time finding the build instructions. Could you please add this to the announcement? ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion

Re: [Numpy-discussion] ANN: NumPy 1.8.0 release.

Charles R Harris wrote: On Thu, Oct 31, 2013 at 6:58 AM, Neal Becker ndbeck...@gmail.com wrote: Thanks for the release! I am having a hard time finding the build instructions. Could you please add this to the announcement? What sort of build instructions are you looking for? Chuck

[Numpy-discussion] strange behavior of += with object array

import numpy as np #from accumulator import stat2nd_double ## Just to make this really clear, I'm making a dummy ## class here that overloads += class stat2nd_double (object): def __iadd__ (self, x):

[Numpy-discussion] is np vector a sequence?

isinstance (np.zeros (10), collections.Sequence) Out[36]: False That's unfortunate. ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion

Re: [Numpy-discussion] Valid algorithm for generating a 3D Wiener Process?

David Goldsmith wrote: Is this a valid algorithm for generating a 3D Wiener process? (When I graph the results, they certainly look like potential Brownian motion tracks.) def Wiener3D(incr, N): r = incr*(R.randint(3, size=(N,))-1) r[0] = 0 r = r.cumsum() t =

[Numpy-discussion] openblas?

Does numpy/scipy support building with openblas for blas,lapack instead of atlas? ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion

[Numpy-discussion] my code (python version)

Here's code I use for basic 2d histogramimport numpy as np def nint (x): if x = 0: return int (x + 0.5) else: return int (x - 0.5) class histogram2d (object): def __init__ (self, min, max, delta, clip=True): self.min = min self.max = max

Re: [Numpy-discussion] ANN: 1.8.0b2 release.

Charles R Harris wrote: Hi all, I'm happy to announce the second beta release of Numpy 1.8.0. This release should solve the Windows problems encountered in the first beta. Many thanks to Christolph Gohlke and Julian Taylor for their hard work in getting those issues settled. It would be

Re: [Numpy-discussion] numpy 1.8.0b1 mkl test_xerbla failure

Charles R Harris wrote: On Thu, Sep 5, 2013 at 5:34 AM, Neal Becker ndbeck...@gmail.com wrote: Just want to make sure this post had been noted: Neal Becker wrote: Built on fedora linux 19 x86_64 using mkl: build OK using: env ATLAS=/usr/lib64 FFTW=/usr/lib64 BLAS=/usr/lib64 LAPACK

[Numpy-discussion] numpy 1.8.0b1 mkl test_xerbla failure

Just want to make sure this post had been noted: Neal Becker wrote: Built on fedora linux 19 x86_64 using mkl: build OK using: env ATLAS=/usr/lib64 FFTW=/usr/lib64 BLAS=/usr/lib64 LAPACK=/usr/lib64 CFLAGS=-mtune=native -march=native -O3 LDFLAGS=-Wl,- rpath=/opt/intel/mkl/lib/intel64

Re: [Numpy-discussion] ANN: Scipy 0.13.0 beta 1 release

Failed building on fedora 19 x86_64 using atlas: creating build/temp.linux-x86_64-2.7/numpy/linalg creating build/temp.linux-x86_64-2.7/numpy/linalg/lapack_lite compile options: '-DATLAS_INFO=\3.8.4\ -I/usr/include -Inumpy/core/include - Ibuild/src.linux-x86_64-2.7/numpy/core/include/numpy

Re: [Numpy-discussion] ANN: Numpy 1.8.0 beta 1 release

Built on fedora linux 19 x86_64 using mkl: build OK using: env ATLAS=/usr/lib64 FFTW=/usr/lib64 BLAS=/usr/lib64 LAPACK=/usr/lib64 CFLAGS=-mtune=native -march=native -O3 LDFLAGS=-Wl,- rpath=/opt/intel/mkl/lib/intel64 python setup.py build and attached site.cfg:

Re: [Numpy-discussion] ANN: Scipy 0.13.0 beta 1 release

David Cournapeau wrote: On Wed, Sep 4, 2013 at 1:00 PM, Neal Becker ndbeck...@gmail.com wrote: Failed building on fedora 19 x86_64 using atlas: creating build/temp.linux-x86_64-2.7/numpy/linalg creating build/temp.linux-x86_64-2.7/numpy/linalg/lapack_lite compile options: '-DATLAS_INFO

[Numpy-discussion] lots of warnings with python3

I tried running python2 -3 on some code, and found numpy produces a lot of warnings. Many like: python -3 -c 'import numpy' ... /usr/lib64/python2.7/site-packages/numpy/lib/polynomial.py:928: DeprecationWarning: Overriding __eq__ blocks inheritance of __hash__ in 3.x But also:

[Numpy-discussion] forwarded article (embracing tensors)

I thought the topic of this article might be of interest here: https://groups.google.com/forum/?fromgroups#!topic/julia-dev/GAdcYzmibyo ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion

[Numpy-discussion] another indexing question

I have a system that transmits signals for an alphabet of M symbols over and additive Gaussian noise channel. The receiver has a 1-d array of complex received values. I'd like to find the means of the received values according to the symbol that was transmitted. So transmit symbol indexes might

Re: [Numpy-discussion] RuntimeWarning: divide by zero encountered in log

Nathaniel Smith wrote: On 16 May 2013 19:48, Jonathan Helmus jjhel...@gmail.com wrote: On 05/16/2013 01:42 PM, Neal Becker wrote: Is there a way to get a traceback instead of just printing the line that triggered the error? ___ NumPy

Re: [Numpy-discussion] somewhat less stupid problem with 0-d arrays

Sebastian Berg wrote: On Fri, 2013-05-10 at 19:57 -0400, Neal Becker wrote: It would be convenient if in arithmetic 0-d arrays were just ignored - it would seem to me to be convenient in generic code where a degenerate array is treated as nothing Small naming detail. A 0-d array

[Numpy-discussion] 0-dim arrays inconsistency

np.array ((0,0)) Out[10]: array([0, 0]) ok, it's 2 dimensional In [11]: np.array ((0,0)).shape Out[11]: (2,) except, it isn't ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion

Re: [Numpy-discussion] 0-dim arrays inconsistency

Neal Becker wrote: np.array ((0,0)) Out[10]: array([0, 0]) ok, it's 2 dimensional In [11]: np.array ((0,0)).shape Out[11]: (2,) except, it isn't Sorry for the stupid question - please ignore ___ NumPy-Discussion mailing list NumPy-Discussion

[Numpy-discussion] somewhat less stupid problem with 0-d arrays

It would be convenient if in arithmetic 0-d arrays were just ignored - it would seem to me to be convenient in generic code where a degenerate array is treated as nothing np.zeros ((0,0)) + np.ones ((2,2)) --- ValueError

[Numpy-discussion] what do I get if I build with MKL?

What sorts of functions take advantage of MKL? Linear Algebra (equation solving)? Something like dot product? exp, log, trig of matrix? basic numpy arithmetic? (add matrixes) ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org

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