Mailman 3 May 2012 - SciPy-Dev

relative imports
by Denis Laxalde May 16, 2012

May 16, 2012

Hi, What do people think about using relative imports [1] within scipy modules? One advantage I can see is to allow packages to be built and tested independently. Any drawbacks? [1]: http://docs.python.org/whatsnew/2.5.html#pep-328-absolute-and-relative-impo… -- Denis

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prepending underscores to private module names
by Ralf Gommers May 16, 2012

May 16, 2012

Hi, A while ago we discussed making a clear distinction between public and private modules by using underscores consistently, see http://thread.gmane.org/gmane.comp.python.scientific.devel/14936. I've done this for a few modules now, see https://github.com/rgommers/scipy/tree/underscores. Most files could simply be underscored, some other would conflict with extension modules so I also had to append _py to the name. Also I added a file doc/source/api.rst that states which modules are public (up for discussion of course). With google code search I checked how common it is to import from modules that are supposed to be private, for example "from scipy.optimize.optimize import fmin". It's not very common but does happen, so deprecation warnings should be put in. Before going further I'd like to check that this looks okay to people. What do you think? Cheers, Ralf <https://github.com/rgommers/scipy/tree/underscores>

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ipython notebook for docs/examples
by alex arsenovic May 15, 2012

May 15, 2012

i recently took a look at the ipython notebook feature. its awesome. if it is interface-able with sphinx, i could write docs way faster. also, it seems to me that making interactive tutorials/examples with this accesable through a server would work great. has this idea already been considered? if not , does anyone have thoughts on this? alex

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Question about stats.mstats.kendalltau_seasonal
by Andreas H. May 15, 2012

May 15, 2012

Hi, looking at stats.mstats.kendalltau_seasonal, i noticed the lack of proper documentation for that function. I'd like to write something up about it, but wanted to verify that the original author was indeed following the approach in Hirsch, Robert M., and James R. Slack. “A Nonparametric Trend Test for Seasonal Data With Serial Dependence.” Water Resources Research 20, no. 6 (1984): P. 727. (http://www.agu.org/pubs/crossref/1984/WR020i006p00727.shtml) Also, it would be nice to hear what exactly the different return values are. If you guys tell me, I'll gladly write docstring + example. Cheers, Andreas.

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reading a module under test
by nicky van foreest May 15, 2012

May 15, 2012

Hi, I would like to run a test on some code in my local branch of scipy. Now the problem in one of the test files is that it says from scipy import stats Now this reads the standard stats module, not the one I want to test, i.e, the one on my local branch. I changed the pythonpath, but this does not help. Is there a generic way to say something like from scipy import path_to_my_stats_under_test/stats ? Specifically, I want to load this file: /home/nicky/prog/scipy/scipy/stats/distributions.py, and I don't want to load /usr/lib/python2.7/dist-packages/scipy/stats/distributions.py. Thanks for any help. Nicky

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scipy.stats: algorithm to for ticket 1493
by nicky van foreest May 14, 2012

May 14, 2012

Hi, I saw Ralf's suggestions on issues of scipy.stats to work on. In another project I had to solve a similar problem as the one mentioned in http://projects.scipy.org/scipy/ticket/1493. I like to propose the algorithm below to tackle this. I am looking forward to your feedback. Once the algo seems to work impeccably, I'll try to convert it such that it can be incorporated in scipy.stats and add test cases. Lets first test the example of the ticket: In [21]: from scipy.stats import invnorm In [22]: from scipy import optimize In [23]: invnorm.xb = 10 In [24]: sol = invnorm.ppf(0.8455, 7.24000019602, scale= 2.51913630166) In [25]: print sol 25.1878345282 In [26]: print invnorm.cdf(sol, 7.24000019602, scale=2.51913630166) 0.8455 In [27]: Weird that this leads to a solution, as the solution is not in the search interval. Trying xb = 5 leads to the reported error. Now a solution: # Proposed solution. # A quintessential property in the algorithm is that the cdf is an # non-decreasing function. def findppf(q): # search until xb is large enough left, right = invnorm.xa, invnorm.xb while invnorm.cdf(right, 7.24000019602, scale=2.51913630166) < q: left = right right *= 2 return optimize.brentq(lambda x: \ invnorm.cdf(x, 7.24000019602, scale=2.51913630166) - q,\ left, right) # Perhaps increasing with a larger factor than 2 is faster, as brentq # convergest very fast. Taking `right` too large is problably not a real # problem. On the other hand, when `right` increases too fast, cdf(right) may # become numerically equal to 1. So, what would be a good factor? sol = findppf(0.8455) print sol print invnorm.cdf(sol, 7.24000019602, scale=2.51913630166) This code (I ran it in a file, not in ipython) gives the right results, at least for these values. Nicky

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Missing docstrings in the SciPy docstring editor
by Tim Cera May 14, 2012

May 14, 2012

Most of the docstrings are gone from the on-line editor... http://docs.scipy.org/scipy/docs/ Kindest regards, Tim

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Find points in delaunay triangulation : scipy.spatial vs. scipy.interpolation
by Pablo Winant May 13, 2012

May 13, 2012

Hi, I tried to use interpolation routines in scipy recently and I have found two slight performance issues - The LinearNDInterpolation object implemented in cython requires a list of points and a list of values to be created. But is is not documented how to change the values of the interpolator without doing the mesh again. This is useful when one is solving the values of a function at the vertices of the mesh : one doesn't want to do the triangulation again and again. Maybe there could be a simple specific method to set the values in this case. In that case it would consist in changing the value of a property but it would be consistent with more general interpolation schemes. - I tried to use the delaunay object from scipy and noticed a strange thing: for a given set of coordinates it takes longer to get the indices of the triangles containing the points than it takes to perform the interpolation using LinearND object. This is puzzling since apparently the implementation of LinearND performs many calls to the qhull library to get this indices. Attached is a simple exampe demonstrating this anomaly. One last thing: I have written an interpolation object on sparse grids, using smolyak product of chebychev polynomials. It is written in pure python (vectorized) and licensed under the bsd license. Currently it lives in another library but I guess it would make more sense to have something like that in a more general scientific lib. Let me know if you are interested. (it is available there anyway: https://github.com/albop/dynare-python/tree/master/dolo/src/dolo/numeric: chebychev.py and smolyak.py) Best regards, Pablo

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Re: [SciPy-Dev] documentation and sphinx
by TP May 13, 2012

May 13, 2012

On Sat, May 12, 2012 at 12:25 PM, nicky van foreest <vanforeest(a)gmail.com> wrote: > Hi, > > Thanks for your reply. I have a question about using mathjax (I am not > an expert on this, in any way). Currently I write my documentation in > sphinx, then I use >make html. Once the making in finished I ftp the > _build directory to a webserver. Should this webserver run java script > to enable me to use mathjax to render the formulas? > > Nicky No. Only the web browser used to view your site needs to support javascript.

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scipy stats tutorial
by nicky van foreest May 13, 2012

May 13, 2012

Hi, I have rewritten the first part of the scipy tutorial to such a form that it is (hopefully) easy accessible to new user of scipy.stats. To this aim I explicitly discuss loc and scale, and so on. (I recall that as a first time user I had no idea about vectorization, broadcasting, ... and that quite a lot of info was thrown at me at the same time, while I just wanted to compute the cdf of the Poisson distribution.) Since I made numerous changes at the start of the document, checking the differences through diff on github seems a very unattractive job to me. Second, to check whether the mark up was correct, I ran stats.rst through my local sphinx. For these to reasons I attach my local stats.html to this mail, so that you can check the end result. I don't have the plot directive, but I don't think that that is a problem for the moment. I left the sample analyses and the kernel density estimation untouched. I think these are already good enough to stand on their own. Once a user made it through my parts of the tutorial, these topics should be accessible (with sufficient background in statistics). Looking forward to your feedback, Nicky

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