Mailman 3 November 2008 - NumPy-Discussion

Need some explanations on assigning/incrementing values in Numpy
by Loïc BERTHE 24 Nov '08

24 Nov '08

I've encoutered an error during an ipython's session that I fail to understand : In [12]: n = 4 In [13]: K = mat(diag(arange(2*n))) In [14]: print K [[0 0 0 0 0 0 0 0] [0 1 0 0 0 0 0 0] [0 0 2 0 0 0 0 0] [0 0 0 3 0 0 0 0] [0 0 0 0 4 0 0 0] [0 0 0 0 0 5 0 0] [0 0 0 0 0 0 6 0] [0 0 0 0 0 0 0 7]] In [15]: o = 2*arange(n) In [16]: kc = 10 + arange(n) In [17]: K[ r_[o-1, o], r_[o, o-1] ] = r_[kc, kc] In [18]: print K [[ 0 0 0 0 0 0 0 10] [ 0 1 11 0 0 0 0 0] [ 0 11 2 0 0 0 0 0] [ 0 0 0 3 12 0 0 0] [ 0 0 0 12 4 0 0 0] [ 0 0 0 0 0 5 13 0] [ 0 0 0 0 0 13 6 0] [10 0 0 0 0 0 0 7]] In [19]: K[ r_[o-1, o], r_[o, o-1]] += 10*r_[kc, kc] --------------------------------------------------------------------------- <type 'exceptions.ValueError'> Traceback (most recent call last) /home/loic/Python/numpy/<ipython console> in <module>() <type 'exceptions.ValueError'>: array is not broadcastable to correct shape In [20]: print K[ r_[o-1, o], r_[o, o-1]].shape, r_[kc, kc].shape (1, 8) (8,) In [21]: print K[ r_[o-1, o], r_[o, o-1]].shape, r_[kc, kc][newaxis, :].shape (1, 8) (1, 8) In [22]: K[ r_[o-1, o], r_[o, o-1]] += 10*r_[kc, kc][newaxis, :] --------------------------------------------------------------------------- <type 'exceptions.ValueError'> Traceback (most recent call last) /home/loic/Python/numpy/<ipython console> in <module>() <type 'exceptions.ValueError'>: array is not broadcastable to correct shape Could you explain me : - Why do an assignment at line 17 works where an increment raises an error (line 19) ?

3 2

status of numpy 1.3.0
by Jarrod Millman 24 Nov '08

24 Nov '08

Now that scipy 0.7.0b1 has been tagged, I wanted to start planning for the NumPy 1.3.0: http://projects.scipy.org/scipy/numpy/milestone/1.3.0 The original plan was to release 1.3 at the end of November. At this point, we are going to have to push back the release date a bit. I would like to get 1.3 out ASAP, so I would like aim for the third week of December. This is how I see the current development trunk: * 2.6 compatablity (Linux 32- and 64-bit done, Windows 32-bit done, Mac 32-bit done) * Generalized Ufuncs (committed) * Ufunc clean-up (committed) * Refactoring numpy.core math configuration (?? bump to 1.4 ??) * Improvements to build warnings (?? bump to 1.4 ??) * Histogram (committed) * NumPy testing improvements (http://projects.scipy.org/scipy/numpy/ticket/957) * Documentation improvements * MaskedArray improvements * Bugfixes Am I missing anything? Is there anything else that we should get in before releasing 1.3? Does it seem reasonable that we could release 1.3 during the third week of December? Who will have time to work on NumPy for the next month? Thanks, -- Jarrod Millman Computational Infrastructure for Research Labs 10 Giannini Hall, UC Berkeley phone: 510.643.4014 http://cirl.berkeley.edu/

6 6

Numpy 1.2.2 ?
by Pierre GM 24 Nov '08

24 Nov '08

All, I've recently introduced some little fixes in the SVN version of numpy.ma.core Is there any plan for a 1.2.2 release, or will we directly switch to 1.3.0 ? Do I need to backport these fixes to 12x ? Thx a lot in advance P.

3 4

Stop generating include files?
by Charles R Harris 24 Nov '08

24 Nov '08

Hi All, I would like to suggest that it is time to stop generating the include files by scanning the (c) sources. I think this would be a good thing to do for the following reasons. 1. The Numpy API has settled down and we shouldn't be changing is much. 2. It is good practice to separate the declarations and definitions so that they act as checks on one another. 3. It simplifies the build system. Instead of lists of scanned files, lists of API order, and a generator, we simply have *.h files. 4. A simplified build system makes it easier to break up files and generate API functions from code templates. 5. The *.h files will be available in Numpy *before* a build. This should make it easier for newbies to figure out what is going on. I don't suggest we remove the various API tags, they are useful bits of documentation when reading the code. Chuck

1 0

numpy.ma.mod missing
by Charles سمير Doutriaux 23 Nov '08

23 Nov '08

Hello, Can I request that "mod" be added to numpy.ma ? Thx, C>

2 1

MATLAB ASCII format
by Gideon Simpson 22 Nov '08

22 Nov '08

Is there (or should there be) a routine for reading and writing numpy arrays and matrices in MATLAB ASCII m-file format? -gideon

2 1

numpy.ma.allclose bug
by Charles سمير Doutriaux 21 Nov '08

21 Nov '08

The following shows a bug in numpy.ma.allclose: import numpy import numpy.ma a = numpy.arange(100) b=numpy.reshape(a,(10,10)) print b c=numpy.ma.masked_greater(b,98) print c.count() numpy.ma.allclose(b,1) numpy.ma.allclose(c,1) Since c is masked it fails I think it should pass returning either False or True, not sure what it should return in case all the elements are equal to 1 (except of course the masked one) Note that the following works: numpy.ma.allclose(c,numpy.ma.ones(c.shape)) So I'm good for now Thanks, C>

2 1

Building numpy on Windows 64-bit BLAS/LAPACK
by Hanni Ali 21 Nov '08

21 Nov '08

Hi, I have spent some time trying to use different methods to build numpyon Windows 64bit with a version of BLAS/LAPACK other than the inbuilt one (no slur on the inbuilt one it is excellent, I am simply attempting to see if there is any alternative with better performance). The most recent i have tried is from here: http://icl.cs.utk.edu/lapack-for-windows/index.html I used the installer and set the site.cfg file up in the following manner: [blas] library_dirs = C:\Program Files (x86)\University Of Tennessee\LAPACK 3.1.1\lib\x64 blas_libs = BLAS include_dirs = C:\Program Files (x86)\University Of Tennessee\LAPACK 3.1.1\src [lapack] language = f77 lapack_libs = LAPACK library_dirs = C:\Program Files (x86)\University Of Tennessee\LAPACK 3.1.1\lib\x64 include_dirs = C:\Program Files (x86)\University Of Tennessee\LAPACK 3.1.1\src I have installed both intel's and pgi's fortran compilers in an attempt to get numpy to complete a compilation using these libraries, but have not been successful, both trip up at this point: lapack_litemodule.obj : warning LNK4197: export 'initlapack_lite' specified mult iple times; using first specification Creating library build\temp.win-amd64-2.6\Release\numpy\linalg\ lapack_lite.li b and object build\temp.win-amd64-2.6\Release\numpy\linalg\lapack_lite.exp lapack_litemodule.obj : error LNK2019: unresolved external symbol dgeev_ referen ced in function lapack_lite_dgeev lapack_litemodule.obj : error LNK2019: unresolved external symbol dsyevd_ refere nced in function lapack_lite_dsyevd lapack_litemodule.obj : error LNK2019: unresolved external symbol zheevd_ refere nced in function lapack_lite_zheevd lapack_litemodule.obj : error LNK2019: unresolved external symbol dgelsd_ refere nced in function lapack_lite_dgelsd lapack_litemodule.obj : error LNK2019: unresolved external symbol dgesv_ referen ced in function lapack_lite_dgesv lapack_litemodule.obj : error LNK2019: unresolved external symbol dgesdd_ refere nced in function lapack_lite_dgesdd lapack_litemodule.obj : error LNK2019: unresolved external symbol dgetrf_ refere nced in function lapack_lite_dgetrf lapack_litemodule.obj : error LNK2019: unresolved external symbol dpotrf_ refere nced in function lapack_lite_dpotrf lapack_litemodule.obj : error LNK2019: unresolved external symbol dgeqrf_ refere nced in function lapack_lite_dgeqrf lapack_litemodule.obj : error LNK2019: unresolved external symbol dorgqr_ refere nced in function lapack_lite_dorgqr lapack_litemodule.obj : error LNK2019: unresolved external symbol zgeev_ referen ced in function lapack_lite_zgeev lapack_litemodule.obj : error LNK2019: unresolved external symbol zgelsd_ refere nced in function lapack_lite_zgelsd lapack_litemodule.obj : error LNK2019: unresolved external symbol zgesv_ referen ced in function lapack_lite_zgesv lapack_litemodule.obj : error LNK2019: unresolved external symbol zgesdd_ refere nced in function lapack_lite_zgesdd lapack_litemodule.obj : error LNK2019: unresolved external symbol zgetrf_ refere nced in function lapack_lite_zgetrf lapack_litemodule.obj : error LNK2019: unresolved external symbol zpotrf_ refere nced in function lapack_lite_zpotrf lapack_litemodule.obj : error LNK2019: unresolved external symbol zgeqrf_ refere nced in function lapack_lite_zgeqrf lapack_litemodule.obj : error LNK2019: unresolved external symbol zungqr_ refere nced in function lapack_lite_zungqr build\lib.win-amd64-2.6\numpy\linalg\lapack_lite.pyd : fatal error LNK1120: 18 u nresolved externals error: Command "C:\Program Files (x86)\Microsoft Visual Studio 9.0\VC\BIN\amd64\ link.exe /DLL /nologo /INCREMENTAL:NO /LIBPATH:"C:\Program Files (x86)\Universit y Of Tennessee\LAPACK 3.1.1\lib\x64" /LIBPATH:C:\Python26\libs /LIBPATH:C:\Pytho n26\PCbuild\amd64 LAPACKd.lib BLASd.lib /EXPORT:initlapack_lite build\temp.win-a md64-2.6\Release\numpy\linalg\lapack_litemodule.obj /OUT:build\lib.win-amd64-2.6 \numpy\linalg\lapack_lite.pyd /IMPLIB:build\temp.win-amd64-2.6\Release\numpy\lin alg\lapack_lite.lib /MANIFESTFILE:build\temp.win-amd64-2.6\Release\numpy\linalg\ lapack_lite.pyd.manifest" failed with exit status 1120 I appreciate any help or ideas anyone has, Cheers, Hanni

1 0

can't build numpy 1.2.0 under python 2.6 (windows-amd64) using VS9
by Paul Lucek 20 Nov '08

20 Nov '08

I get the following errors in umathmodule.c.src: D:\Program Files (x86)\Microsoft Visual Studio 9.0\VC\BIN\amd64\cl.exe /c /nolog o /Ox /MD /W3 /GS- /DNDEBUG -Ibuild\src.win-amd64-2.6\numpy\core\src -Inumpy\cor e\include -Ibuild\src.win-amd64-2.6\numpy\core\include/numpy -Inumpy\core\src -I numpy\core\include -Id:\python26\include -Id:\python26\PC /Tcbuild\src.win-amd64 -2.6\numpy\core\src\umathmodule.c /Fobuild\temp.win-amd64-2.6\Release\build\src. win-amd64-2.6\numpy\core\src\umathmodule.obj umathmodule.c numpy\core\src\umathmodule.c.src(64) : error C2059: syntax error : 'type' numpy\core\src\umathmodule.c.src(70) : error C2059: syntax error : 'type' numpy\core\src\ufuncobject.c(1701) : warning C4244: '=' : conversion from 'npy_i ntp' to 'int', possible loss of data numpy\core\src\ufuncobject.c(2422) : warning C4244: '=' : conversion from 'npy_i ntp' to 'int', possible loss of data error: Command "D:\Program Files (x86)\Microsoft Visual Studio 9.0\VC\BIN\amd64\ cl.exe /c /nologo /Ox /MD /W3 /GS- /DNDEBUG -Ibuild\src.win-amd64-2.6\numpy\core \src -Inumpy\core\include -Ibuild\src.win-amd64-2.6\numpy\core\include/numpy -In umpy\core\src -Inumpy\core\include -Id:\python26\include -Id:\python26\PC /Tcbui ld\src.win-amd64-2.6\numpy\core\src\umathmodule.c /Fobuild\temp.win-amd64-2.6\Re lease\build\src.win-amd64-2.6\numpy\core\src\umathmodule.obj" failed with exit s tatus 2

8 22

contiguous regions
by John Hunter 20 Nov '08

20 Nov '08

I frequently want to break a 1D array into regions above and below some threshold, identifying all such subslices where the contiguous elements are above the threshold. I have two related implementations below to illustrate what I am after. The first "crossings" is rather naive in that it doesn't handle the case where an element is equal to the threshold (assuming zero for the threshold in the examples below). The second is correct (I think) but is pure python. Has anyone got a nifty numpy solution for this? import numpy as np import matplotlib.pyplot as plt t = np.arange(0.0123, 2, 0.05) s = np.sin(2*np.pi*t) def crossings(x): """ return a list of (above, ind0, ind1). ind0 and ind1 are regions such that the slice x[ind0:ind1]>0 when above is True and x[ind0:ind1]<0 when above is False """ N = len(x) crossings = x[:-1]*x[1:]<0 ind = np.nonzero(crossings)[0]+1 lastind = 0 data = [] for i in range(len(ind)): above = x[lastind]>0 thisind = ind[i] data.append((above, lastind, thisind)) lastind = thisind # put the one past the end index if not already in if len(data) and data[-1]!=N-1: data.append((not data[-1][0], thisind, N)) return data def contiguous_regions(mask): """ return a list of (ind0, ind1) such that mask[ind0:ind1].all() is True and we cover all such regions """ in_region = None boundaries = [] for i, val in enumerate(mask): if in_region is None and val: in_region = i elif in_region is not None and not val: boundaries.append((in_region, i)) in_region = None if in_region is not None: boundaries.append((in_region, i+1)) return boundaries fig = plt.figure() ax = fig.add_subplot(111) ax.set_title('using crossings') ax.plot(t, s, 'o') ax.axhline(0) for above, ind0, ind1 in crossings(s): if above: color='green' else: color = 'red' tslice = t[ind0:ind1] ax.axvspan(tslice[0], tslice[-1], facecolor=color, alpha=0.5) fig = plt.figure() ax = fig.add_subplot(111) ax.set_title('using contiguous regions') ax.plot(t, s, 'o') ax.axhline(0) for ind0, ind1 in contiguous_regions(s>0): tslice = t[ind0:ind1] ax.axvspan(tslice[0], tslice[-1], facecolor='green', alpha=0.5) for ind0, ind1 in contiguous_regions(s<0): tslice = t[ind0:ind1] ax.axvspan(tslice[0], tslice[-1], facecolor='red', alpha=0.5) plt.show()

2 1