Mailman 3 December 2010 - NumPy-Discussion

new quarterly OpenOpt/FuncDesigner release 0.32
by Dmitrey Dec. 15, 2010

Dec. 15, 2010

Hi all, I'm glad to inform you about new quarterly OpenOpt/FuncDesigner release (0.32): OpenOpt: * New class: LCP (and related solver) * New QP solver: qlcp * New NLP solver: sqlcp * New large-scale NSP (nonsmooth) solver gsubg. Currently it still requires lots of improvements (especially for constraints - their handling is very premature yet and often fails), but since the solver sometimes already works better than ipopt, algencan and other competitors it was tried with, I decided to include the one into the release. * Now SOCP can handle Ax <= b constraints (and bugfix for handling lb <= x <= ub has been committed) * Some other fixes and improvements > FuncDesigner: * Add new function removeAttachedConstraints * Add new oofuns min and max (their capabilities are quite restricted yet) * Systems of nonlinear equations: possibility to assign personal tolerance for an equation * Some fixes and improvements > > For more details see our forum entry > http://forum.openopt.org/viewtopic.php?id=325 > > Regards, D. >

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Most efficient trim of arrays
by Mark Janikas Dec. 14, 2010

Dec. 14, 2010

Hello All, I was wondering what the best way to trim an array based on some values I do not want.... I could use NUM.where or NUM.take... but let me give you an example: import numpy as NUM n = 100 (Length of my dataset) data = NUM.empty((n,), float) badRecords = [] for ind, record in enumerate(records): if record == someValueIDOntWant: badRecords.append(ind) else: data[ind] = record Now, I want to "trim" my array using badRecords. I guess I want to avoid copying. Any thoughts on the best way to do it? I do not want to use lists and then subsequently array the result as it is nice to pre-allocate the space. Thanks much, MJ

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where to ship libnpymath.a ?
by Sandro Tosi Dec. 14, 2010

Dec. 14, 2010

Hi, in Debian we had a bug report[1] requesting to ship libnpymath.a . [1] http://bugs.debian.org/596987 Our python packaging tools doesn't handle .a files, so I'd like to ask you where exactly should I ship that file. In the build directory I have: $ find . -name "*.a" | xargs md5sum 4c2371b98c138756b0471a4fb364e0ae ./debian/tmp/usr/lib/python2.5/site-packages/numpy/core/lib/libnpymath.a fc6040f2bd4354cca8ef130abc5c8b17 ./debian/tmp/usr/lib/python2.6/dist-packages/numpy/core/lib/libnpymath.a 0c9870a2e5cf61669c92677d9b12c116 ./build/temp_d.linux-x86_64-2.5/libnpymath.a 47fdd29b85570ce80b1c616c6c02f41a ./build/temp.linux-x86_64-2.6-pydebug/libnpymath.a 4c2371b98c138756b0471a4fb364e0ae ./build/temp.linux-x86_64-2.5/libnpymath.a fc6040f2bd4354cca8ef130abc5c8b17 ./build/temp.linux-x86_64-2.6/libnpymath.a (the md5sum is to show that they are actually different between python version and/or debug build): the first 2 are in the "temporary" debian package preparation dir, while the other 4 are for 2.5/2.6 + normal/debug build. So, back to the original question: where should I put libnpymath.a to be useful for our users (main request: new scipy)? maybe in ..../numpy/core/lib/ ? Cheers, -- Sandro Tosi (aka morph, morpheus, matrixhasu) My website: http://matrixhasu.altervista.org/ Me at Debian: http://wiki.debian.org/SandroTosi

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Numpy and Python3
by Katharina Dec. 12, 2010

Dec. 12, 2010

Hello everyone, first, I'm really apologise for my English-skills. But I have only one simple questions. Does NumPy work on Python3 now. I read so many articles on the Internet, but you can only read some speculation and not a clear state about this topic. At the moment I try numpy1.5.1 on Python3.0, but I get only Errors. If Numpy works on Python3, are the support libraries the same as by Python2.6? (By the way, I use Linux (Ubuntu 9.04)) /With kind regards Ingwer

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[ANN] FOSDEM datadevroom - Feb. 5 2011 - Brussels - Call for Presentations
by Olivier Grisel Dec. 12, 2010

Dec. 12, 2010

Hello numpy users, We (Isabel Drost, Nicolas Maillot and I) are organizing a Data Analytics Devroom that will take place during the next edition of the FOSDEM in Brussels on Feb. 5. Here is the CFP: http://datadevroom.couch.it/CFP You might be interested in attending the event and take the opportunity to speak about your projects. Important Dates (all dates in GMT +2): Submission deadline: 2010-12-17 Notification of accepted speakers: 2010-12-20 Publication of final schedule: 2011-01-10 Meetup: 2011-02-05 The event will comprise presentations on scalable data processing. We invite you to submit talks on the topics: Information retrieval / Search Large Scale data processing, Machine Learning, Text Mining, Computer vision, [Linked] Open Data. High quality, technical submissions are called for, ranging from principles to practice. We are looking for presentations on the implementation of the systems themselves, real world applications and case studies. Submissions should be based on free software solutions. Please re-distribute this CFP to people who might be interested. Looking forward to meeting you face to face in Brussels, -- Olivier http://twitter.com/ogrisel - http://github.com/ogrisel

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np.lookfor -- still supported / working ?
by Sebastian Haase Dec. 11, 2010

Dec. 11, 2010

Hi all, I recently discovered numpy's lookfor function, which is supposed to look through "all kinds" of doc strings and list relevant functions related to given keywords. However it does not seem to work for me: >>> N.__version__ '1.3.0' >>> N.lookfor('fft', module=None, import_modules=True, regenerate=False) Traceback (most recent call last): File "<input>", line 1, in <module> File "C:\cygwin\home\haase\Priithon_25_win\numpy\lib\utils.py", line 622, in lookfor found.sort(relevance_sort) TypeError: comparison function must return int >>> 1/2 # I use from future import division .... 0.5 >>> I especially like, that it is supposed to work for any other (not just numpy or scipy) module. But that also doesn't work: >>> import wx >>> N.lookfor('background', module='wx', import_modules=True, regenerate=False) Traceback (most recent call last): File "<input>", line 1, in <module> File "C:\cygwin\home\haase\Priithon_25_win\numpy\lib\utils.py", line 574, in lookfor cache = _lookfor_generate_cache(module, import_modules, regenerate) File "C:\cygwin\home\haase\Priithon_25_win\numpy\lib\utils.py", line 729, in _lookfor_generate_cache doc = inspect.getdoc(item) File "C:\cygwin\home\haase\Priithon_25_win\Python25\lib\inspect.py", line 313, in getdoc doc = object.__doc__ NameError: Unknown C global variable >>> I tried it on more recent numpy (1.5.1 I think) and got same problems. Any comments ? Thanks, Sebastian Haase

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np.var() and ddof
by Keith Goodman Dec. 10, 2010

Dec. 10, 2010

Why does ddof=2 and ddof=3 give the same result? >> np.var([1, 2, 3], ddof=0) 0.66666666666666663 >> np.var([1, 2, 3], ddof=1) 1.0 >> np.var([1, 2, 3], ddof=2) 2.0 >> np.var([1, 2, 3], ddof=3) 2.0 >> np.var([1, 2, 3], ddof=4) -2.0 I expected NaN for ddof=3.

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A Cython apply_along_axis function
by Keith Goodman Dec. 10, 2010

Dec. 10, 2010

It's hard to write Cython code that can handle all dtypes and arbitrary number of dimensions. The former is typically dealt with using templates, but what do people do about the latter? I'm trying to take baby steps towards writing an apply_along_axis function that takes as input a cython function, numpy array, and axis. I'm using the following numpy ticket as a guide but I'm really just copying and pasting without understanding: http://projects.scipy.org/numpy/attachment/ticket/1213/_selectmodule.pyx Can anyone spot why I get a segfault on the call to nanmean_1d in apply_along_axis? import numpy as np cimport numpy as np import cython cdef double NAN = <double> np.nan ctypedef np.float64_t (*func_t)(void *buf, np.npy_intp size, np.npy_intp s) def apply_along_axis(np.ndarray[np.float64_t, ndim=1] a, int axis): cdef func_t nanmean_1d cdef np.npy_intp stride, itemsize cdef int ndim = a.ndim cdef np.float64_t out itemsize = <np.npy_intp> a.itemsize if ndim == 1: stride = a.strides[0] // itemsize # convert stride bytes --> items out = nanmean_1d(a.data, a.shape[0], stride) else: raise ValueError("Not yet coded") return out cdef np.float64_t nanmean_1d(void *buf, np.npy_intp n, np.npy_intp s): "nanmean of buffer." cdef np.float64_t *a = <np.float64_t *> buf # cdef np.npy_intp i, count = 0 cdef np.float64_t asum, ai if s == 1: for i in range(n): ai = a[i] if ai == ai: asum += ai count += 1 else: for i in range(n): ai = a[i*s] if ai == ai: asum += ai count += 1 if count > 0: return asum / count else: return NAN

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truth value of dtypes
by Nils Becker Dec. 10, 2010

Dec. 10, 2010

Hi, why is >>> bool(np.dtype(np.float)) False ? I came across this when using this python idiom: def f(dtype=None): ....if not dtype: ........print 'using default dtype' If there is no good reason to have a False truth value, I would vote for making it True since that is what one would expect (no?) N.

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status of date-times
by Mark Bakker Dec. 10, 2010

Dec. 10, 2010

Hello List, Can someone update us on the status of the date-times datatype? Is it working yet? If not, what are the plans? I really appreciate all the work and am looking forward to using the new date-times, Best regards, Mark

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