Mailman 3 September 2006 - SciPy-User

problem with interp1d
by John Hunter Sept. 12, 2006

Sept. 12, 2006

I thought the following code would resample the irregularly spaced 't' to the regularly spaced 'newt' but I am getting a traceback import scipy import scipy.interpolate t = scipy.cumsum(scipy.randn(100)) # increasing time s = scipy.sin(2*scipy.pi*t) interp = scipy.interpolate.interp1d(t, s) newt = scipy.arange(min(t), max(t), 0.1) news = interp(newt) > python tst.py Traceback (most recent call last): File "tst.py", line 7, in ? news = interp(newt) File "/usr/lib/python2.4/site-packages/scipy/interpolate/interpolate.py", line 154, in __call__ out_of_bounds = self._check_bounds(x_new) File "/usr/lib/python2.4/site-packages/scipy/interpolate/interpolate.py", line 208, in _check_bounds raise ValueError, " A value in x_new is below the"\ ValueError: A value in x_new is below the interpolation range. In [2]: scipy.__version__ Out[2]: '0.5.2.dev2196' Any ideas? Thanks, JDH

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Polynomials in several variables
by Neilen Marais Sept. 12, 2006

Sept. 12, 2006

Hi Just wondering if a module similar to the older Scientific Python multivariate polynomial module (Scientific.Functions.Polynomial) is in scipy. It works similar to the 1d polynomial functions except that an n-dimensional array of coeficients are passed in for a polynomial in n variables. Thanks Neilen -- you know its kind of tragic we live in the new world but we've lost the magic -- Battery 9 (www.battery9.co.za)

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NumPy Newcomer Questions: Reading Data Stream & Building Array
by Rich Shepard Sept. 11, 2006

Sept. 11, 2006

After decades of Fortran and C, I'm quite new to Python and all the great tools it provides. So, I'd like mentoring in how to most elegantly and effectively parse data read over a serial port from a scanner, and how to build a 2D array from it. After this, I'll probably need help in other NumPy array (matrix) manipulations. But, first things first: Data are entered on an optical mark readable (OMR) form, which is scanned and the data sent over a serial line. Each form read transmits 69 bytes; there are 2 bytes for each "column" (where there is a timing mark on the edge of the form) and their position within that column determines their value. The form has two blank lines (with timing marks) and three lines with labels; these transmit the equivalent of '0' and are not recorded. The final byte is a carriage return, '\r,' which is translated into a newline ('\n') by the method. For each form read I want to record the form number (programmatically sequentially assigned, starting with '1') and the data from the form as a row. The total forms read then fill a two-dimensional array. The two issues with which I would like help are: How to slice the list of data from the scanner stream into two-byte chunks (leaving the end-of-record byte to be dealt with separately), How to build the array so that each form read creates a new row in the array. While the 31 columns are fixed, the number of rows is indeterminate until all submitted forms have been read. I've attached the 95-line 'OnScan.py' to this message; it's a single function within the application. TIA, Rich -- Richard B. Shepard, Ph.D. | The Environmental Permitting Applied Ecosystem Services, Inc.(TM) | Accelerator <http://www.appl-ecosys.com> Voice: 503-667-4517 Fax: 503-667-8863

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problem with scipy.stats.distributions ?
by PGM Sept. 9, 2006

Sept. 9, 2006

Hello, I recently update to numpy 1.0b5 and scipy 0.5.1, and I'm running into this message: #.................................................................... >>> scipy.stats.distributions.norm.ppf(0.95) --------------------------------------------------------------------------- /usr/lib64/python2.4/site-packages/scipy/stats/distributions.py in ppf(self, q, *args, **kwds) 551 place(output,cond2,self.b*scale + loc) 552 goodargs = argsreduce(cond, *((q,)+args+(scale,loc))) --> 553 scale, loc, goodargs = goodargs[-2], goodargs[-1], goodargs[:-2] 554 place(output,cond,self._ppf(*goodargs)*scale + loc) 555 return output /usr/lib64/python2.4/site-packages/numpy/lib/function_base.py in insert(arr, obj, values, axis) 1165 if (obj < 0): obj += N 1166 if (obj < 0 or obj >=N): -> 1167 raise ValueError, "index (%d) out of range (0<=index<=%d) "\ 1168 "in dimension %d" % (obj, N, axis) 1169 newshape[axis] += 1; ValueError: index (1) out of range (0<=index<=1) in dimension 0 #.................................................................. Would anybody have any idea of what it means ? Thx in advance P.

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Re: [SciPy-user] SciPy-user Digest, Vol 37, Issue 6
by Brendan Simons Sept. 8, 2006

Sept. 8, 2006

That's OK William. I gave it some more thought, and I don't think there's any sparse storage scheme which would allow me to do constant or log time slicing over two axes. The results from slicing the first axis would always have to be sorted, or individually tested, giving on average a complexity of O(n*log(n)) for the one axis sort and O(k*(log(n) + n/2)) for the lookups, where n is the number of intervals, and k is the number of stab inquiries. Since both k and n are high for my case, I've decided to go the traditional route and use an interval tree, which has a complexity of O(n*log(n)) for pre-processing, and only O(k * log(n)) for the lookups. Thanks anyway, Brendan ------------------------------ Message: 5 Date: Fri, 8 Sep 2006 07:52:14 +0200 From: "William Hunter" <willemjagter(a)gmail.com> Subject: Re: [SciPy-user] Efficient submatrix of a sparse matrix To: "SciPy Users List" <scipy-user(a)scipy.org> Message-ID: <8b3894bc0609072252k6f5cdee5p367695c3dd96371f(a)mail.gmail.com> Content-Type: text/plain; charset=UTF-8; format=flowed Brendan; It occured to me after I sent the mail that you're probably not into solving sparse systems, but actually just slicing sparse matrices... If so, my previous post is obviously not of much meaning to you. -- WH On 07/09/06, Brendan Simons <brendansimons(a)yahoo.ca> wrote: > Hi all, > > I have a neat little problem for which I think sparse matrices are > the answer. I need to store a bunch of overlapping "intervals", (a, > b pairs for which any a <= val < b crosses that interval) in a manner > which makes "stabbing inquiries" (which intervals cross a specified > value) easy. The canonical way to to this is with interval trees (a > good summary here: http://w3.jouy.inra.fr/unites/miaj/public/vigneron/ > cs4235/l5cs4235.pdf), however I think I can simplify things as follows: > > 1) perform an argsort on the interval a and b endpoints. This gives > the position of each interval in an "order" matrix M, where each row > and each column contains only one interval, and intervals are sorted > in rows by start point, and in columns by endpoint > > 2) for a "stab" point x, do a binary search to find the row i and > column j where x could be inserted into M and maintain its ordering. > The submatrix of M[:i, j:] would contains all those intervals which > start before x, and end after x. > > Since the order matrix M is mostly empty it would make sense to use a > sparse matrix storage scheme, however the only one in scipy.sparse > that allows 2d slicing is the dok_matrix, and the slicing algorithm > is O(n), which is much too expensive for my purposes (I have to do > thousands of stabbing inquiries on a space containing thousands of > intervals). > > Is there no more efficient algorithm for 2d slicing of a sparse matrix? > > -Brendan > -- > Brendan Simons > __________________________________________________ > Do You Yahoo!? > Tired of spam? Yahoo! Mail has the best spam protection around > http://mail.yahoo.com > _______________________________________________ > SciPy-user mailing list > SciPy-user(a)scipy.org > http://projects.scipy.org/mailman/listinfo/scipy-user >

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Re: [SciPy-user] Interpolate 1D (2D)
by Maik Trömel Sept. 8, 2006

Sept. 8, 2006

Thanks for your help! But there was still the same problem: /usr/lib/python2.3/site-packages/scipy/interpolate/interpolate.py in __call__(self, x, y, dx, dy) 62 x = atleast_1d(x) 63 y = atleast_1d(y) ---> 64 z,ier=fitpack._fitpack._bispev(*(self.tck+[x,y,dx,dy])) 65 if ier==10: raise ValueError,"Invalid input data" 66 if ier: raise TypeError,"An error occurred" AttributeError: interp2d instance has no attribute 'tck' I tried it on another system, but there ist the same problem. But there were the same scipy and numpy verions. So, I've updated to the same scipy and numpy version like you. New (or same?) problem: /usr/lib/python2.3/site-packages/scipy/interpolate/interpolate.py in __call__(self, x, y, dx, dy) 62 Output: 63 z - 2-d array of interpolated values of shape (len(y), len(x)). ---> 64 """ 65 x = atleast_1d(x) 66 y = atleast_1d(y) AttributeError: interp2d instance has no attribute 'tck' ?????????????????? Where's the problem? Anybody an idea? Greetings Maik Maik Trömel wrote: > Message: 8 > Date: Thu, 7 Sep 2006 23:09:42 +1200 > From: "Angus McMorland" <amcmorl(a)gmail.com> > Subject: Re: [SciPy-user] Interpolate 1D > To: "SciPy Users List" <scipy-user(a)scipy.org> > Message-ID: > <e85f13c40609070409j5fe83995jecb473f07fe9ad5(a)mail.gmail.com> > Content-Type: text/plain; charset="iso-8859-1" > > Hi Maik, > > On 07/09/06, Maik Tr?mel <maik.troemel(a)maitro.net> wrote: > >> > >> > Hello, >> > > > <snip> > > I also tried out scipy.interpolate.interpolate.interp2d. But I get an > >> > error. Probably somebody knows what I'm doing wrong. Here's the >> script: >> > >> > import scipy.interpolate >> > >> > #just some data >> > a = numpy.zeros((4,4), dtype=''Float32') >> > oldx= numpy.arange(4) >> > oldy = numpy.arange(4) >> > newx = numpy.zeros((4), dtype=''Float32') >> > newy =numpy.zeros((4), dtype=''Float32') >> > for s in range(8): >> > newx[s] = s * 0.5 >> > newy[s] = s * 0.5 >> > >> > #interpolation >> > intinst = scipy.interpolate.interpolate.interp2d(oldx, oldy, a, kind = >> > 'cubic') >> > interpolated = intinst(newx, newy) >> > >> > >> > And here's the error: >> > /usr/lib/python2.3/site-packages/scipy/interpolate/interpolate.py in >> > __call__(self, x, y, dx, dy) >> > 62 x = atleast_1d(x) >> > 63 y = atleast_1d(y) >> > ---> 64 >> z,ier=fitpack._fitpack._bispev(*(self.tck+[x,y,dx,dy])) >> > 65 if ier==10: raise ValueError,"Invalid input data" >> > 66 if ier: raise TypeError,"An error occurred" >> > >> > AttributeError: interp2d instance has no attribute 'tck' >> > >> > Thanks for your help. >> > >> > Greetings Maik >> > > > I've tried your script, and get several different errors, so are you sure > that your error messages are coming from this script? > > The biggest conceptual jump needed with your script, as it runs on my > system, (scipy 0.5.0.2177, numpy 1.0b4.dev3055) is that oldx and oldy > need > to be the same length as the flattened 'a' - that is an (x,y) pair for > each > value of a, which itself could also be flat. Here is, I think, a working > version: > > import scipy.interpolate > import numpy > > #just some data > a = numpy.random.random_sample((4,4)).astype('Float32') > oldinds = numpy.indices((4,4)) > oldx = oldinds[1].flatten() # because indices[1] is the x values > oldy = oldinds[0].flatten() > newx = numpy.linspace(0,3,8).astype('Float32') > newy = numpy.linspace(0,3,8).astype('Float32') > > #interpolation > intinst = scipy.interpolate.interp2d(oldx, oldy, a, kind = 'cubic') > interpolated = intinst(newx, newy) > > #display the result - can ignore if you don't have matplotlib installed > import pylab > > pylab.subplot(121) > pylab.imshow(a,interpolation='nearest') > pylab.subplot(122) > pylab.imshow(interpolated, interpolation='nearest') > > >

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3D plotting in Python
by William Hunter Sept. 8, 2006

Sept. 8, 2006

See http://www.scipy.org/WilnaDuToit for those who are interested, don't think it was posted to this ML. -- WH

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f2py and xmingw
by Flavio Coelho Sept. 8, 2006

Sept. 8, 2006

Hi, I am trying to compile a Fortran extension module for windows using Scipy. I want to know if it is possible to do this with xmingw (from my Gentoo Linux Box) Under Linux I can automate the generation of binary packages with setup.pybdist (and a properly written setup.py) what is the recomended way to generate binary packages(with fortran extensions) for windows? I have tried to run f2y specifying the crosscompilers from xmingw but it failed: command line: f2py -c --compiler=/opt/xmingw/bin/i386-mingw32msvc-gcc --f77exec=opt/xmingw/bin/i386-mingw32msvc-g77 -m flib flib.f Error: error: don't know how to compile C/C++ code on platform 'posix' with '/opt/xmingw/bin/i386-mingw32msvc-gcc' compiler It looks like I may be missing some compiler flags... Since my experience with compiled languages is somewhat limited, I will gladly accept any suggestions. thanks, -- Flávio Codeço Coelho registered Linux user # 386432 --------------------------- "Laws are like sausages. It's better not to see them being made." Otto von Bismark

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ISP changeover Tuesday 9/12 7:00 PM Central
by Jeff Strunk Sept. 7, 2006

Sept. 7, 2006

Good afternoon, Unfortunately, our recent change in internet service providers is not working out. We will be switching to a more reliable provider on Tuesday 9/12 at 7:00 PM Central. Please allow for up to two hours of downtime. I will send an email announcing the start and completion of this maintenance. This will effect all Enthought servers as well as the SciPy server which hosts many Open Source projects. The problem was that our in-building internet service provider neglected to mention that our internet connection was over a wireless link to a different building. This link had very high latency. They have fixed this problem, but we feel that wireless is not stable enough for our needs. In order to provide higher quality service, we will be using 3 bonded T1s from AT&T after this switchover. Please pass this message along to people that I have missed. If you have any questions, please direct them to me. We apologize for the inconvenience. Jeff Strunk Enthought, Inc.

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Re: [SciPy-user] Interpolate 1D
by Maik Trömel Sept. 7, 2006

Sept. 7, 2006

Hello, scipy.interpolate.fitpack2.InterpolatedUnivariateSpline seems to be a 1d interpolation method. I used the Cookbook/Rebinning-Example to Interpolate. I don't know if it works with InterpolatedUnivariateSpline. I also tried out scipy.interpolate.interpolate.interp2d. But I get an error. Probably somebody knows what I'm doing wrong. Here's the script: import scipy.interpolate #just some data a = numpy.zeros((4,4), dtype=''Float32') oldx= numpy.arange(4) oldy = numpy.arange(4) newx = numpy.zeros((4), dtype=''Float32') newy =numpy.zeros((4), dtype=''Float32') for s in range(8): newx[s] = s * 0.5 newy[s] = s * 0.5 #interpolation intinst = scipy.interpolate.interpolate.interp2d(oldx, oldy, a, kind = 'cubic') interpolated = intinst(newx, newy) And here's the error: /usr/lib/python2.3/site-packages/scipy/interpolate/interpolate.py in __call__(self, x, y, dx, dy) 62 x = atleast_1d(x) 63 y = atleast_1d(y) ---> 64 z,ier=fitpack._fitpack._bispev(*(self.tck+[x,y,dx,dy])) 65 if ier==10: raise ValueError,"Invalid input data" 66 if ier: raise TypeError,"An error occurred" AttributeError: interp2d instance has no attribute 'tck' Thanks for your help. Greetings Maik Maik Trömel wrote: > Date: Tue, 5 Sep 2006 11:29:49 -0400 > > From: "A. M. Archibald" <peridot.faceted(a)gmail.com> > Subject: Re: [SciPy-user] Interpolate 1D > To: "SciPy Users List" <scipy-user(a)scipy.org> > Message-ID: > <ce557a360609050829n797be48bv81709ad18bed7e0f(a)mail.gmail.com> > Content-Type: text/plain; charset=ISO-8859-1; format=flowed > > On 05/09/06, Maik Tr?mel <maik.troemel(a)maitro.net> wrote: > >> > Hello list, >> > >> > when I try to use scipy.interpolate.interpolate.interp1d( olddims[-1], >> > a, kind='cubic' ) I get an ERROR: >> > >> > File >> > "/usr/lib/python2.3/site-packages/scipy/interpolate/interpolate.py", >> > line 118, in __init__ >> > raise NotImplementedError, "Only linear supported for now. Use "\ >> > NotImplementedError: Only linear supported for now. Use fitpack >> routines >> > for other types. >> > >> > But under >> > >> http://www.scipy.org/doc/api_docs/scipy.interpolate.interpolate.interp1d.ht… >> >> > kind = 'cubic' is listed. Whats wrong with the command? Or is cubic >> not >> > implemented yet? >> > >> > Thanks for your help! >> > > It seems not to be implemented, but you can use > scipy.interpolate.fitpack2.InterpolatedUnivariateSpline to do the same > thing for splines (of various orders). I think it also provides all > the handy extras like derivatives and root-finding. It doesn't seem to > be able to raise exceptions or insert NaNs for out-of-bound values, it > just extrapolates. But otherwise it seems to be the right tool for the > job. > > A. M. Archibald > > > ------------------------------ > > _______________________________________________ > SciPy-user mailing list > SciPy-user(a)scipy.org > http://projects.scipy.org/mailman/listinfo/scipy-user > > > End of SciPy-user Digest, Vol 37, Issue 3 > ***************************************** > >

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