Mailman 3 December 2006 - NumPy-Discussion

sum of two arrays with different shape?
by zhang yunfeng 20 Dec '06

20 Dec '06

Hi, I'm newbie to Numpy. When reading tutorials at http://www.scipy.org/Tentative_NumPy_Tutorial, I found a snippet about addition of two arrays with different shape, Does it make sense? If array shapes are not same, why it doesn't throw out an error? see the code below (taken from the above webpage) array a.shape is (4,) and y.shape is (3,4) and a+y ? ------------------------------------------- >>> y = arange(12) >>> y array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]) >>> y.shape = 3,4 # does not modify the total number of elements >>> y array([[ 0, 1, 2, 3], [ 4, 5, 6, 7], [ 8, 9, 10, 11]]) It is possible to operate with arrays of diferent dimensions as long as they fit well. >>> 3*a # multiply each element of a by 3 array([ 30, 60, 90, 120]) >>> a+y # sum a to each row of y array([[10, 21, 32, 43], [14, 25, 36, 47], [18, 29, 40, 51]]) -------------------------------------------- -- http://my.opera.com/zhangyunfeng

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Profiling numpy ? (parts written in C)
by David Cournapeau 20 Dec '06

20 Dec '06

Hi, Following the discussion on clip and other functions which *may* be slow in numpy, I would like to know if there is a way to easily profile numpy, ie functions which are written in C. For example, I am not sure to understand why a function like take(a, b) with a a double 256x4 array and b a 8000x256 int array takes almost 200 ms on a fairly fast CPU; in the source code, I can see that numpy uses memmove, and I know memmove to be slower than memcpy. Is there an easy way to check that this is coming from memmove (case in which nothing much can be done to improve the situation I guess), and not from something else ? cheers, David

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(no subject)
by Bandler, Derek 19 Dec '06

19 Dec '06

Hi, I would like to get information on the software licenses for numpy & numeric. On the sourceforge home for the packages, the listed license is OSI-Approved Open Source </softwaremap/trove_list.php?form_cat=14> . Is it possible to get more information on this? A copy of the document would be useful. Thank you. Best regards, Derek Bandler

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Subclasses - use of __finalize__
by Colin J. Williams 18 Dec '06

18 Dec '06

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Python 2.5 on win and Gnuplot and alter_code1
by hermann.ruckerbauer＠qimonda.com 18 Dec '06

18 Dec '06

Hello *, Sorry for this maybe stupid question, I might still miss some understanding of pyton or other stuff ... I have problems getting Gnuplot running under python 2.5 on Windows. My understanding is, that Gnuplot requires Numeric. Unfortionally there is only a numeric for python 2.4 available on the net. This binary does not install under python 2.5. Now I checked numpy, and it seems to able to act as replacement for the numeric package. I'm not really sure if this is the old.numeric module (just replace each numeric with numpy.old.numeric) or if this requires some more changes on the source files (e. g. exchang numeric with numpy and change some of the function calls). So I tried to convert my Gnuplot .py files with the alter_code1. But somehow I'm too stupid to get it running . First absolutel nothing happende when doing e.g. import numpy.oldnumeric.alter_code1 as noa noa.converttree(<top_level>) No error message, but also no file was touched, altough the command took a while to be executed. As I had no idea how to give the top level I tried a little bit around and copied the alter_code1.py into the gnuplot directory. And this file was touched ... It got the comment: At the beginning of alter_code1.py, but non of the other files have been touched. After some copy and paste trials i added on all .py files in the Gnuplot folder the comment from the beginning of the alter_code1.py. And now magically all files in this folders have been touched by running the converttree. BUT: only the comment "## Automatically adapted for numpy.oldnumeric Dec 15, 2006 by " Was added at the beginning of each file, none of the commands have been touched ... Does anybody have some hints for me to get gnuplot running under python 2.5 for windows ? Thanks and regards Hermann

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Re: [Numpy-discussion] Unexpected output usingnumpy.ndarray and__radd__
by Mark Hoffmann 18 Dec '06

18 Dec '06

Excellent, thank you - it solved the problem! /Mark -----Original Message----- From: numpy-discussion-bounces(a)scipy.org [mailto:numpy-discussion-bounces@scipy.org] On Behalf Of Tim Hochberg Sent: 18. december 2006 14:06 To: Discussion of Numerical Python Subject: Re: [Numpy-discussion] Unexpected output usingnumpy.ndarray and__radd__ Mark Hoffmann wrote: > I appreciate the answer and the solution suggestion. I see that it is possible to make a work around by subclassing from ndarray. Still, in the "print a+c" statement, I don't understand why a.__add__(c) doesn't return NotImplemented (because ndarray shouldn't recognize the Cyclehist class) and directly call c.__radd__(a) implemented in my Cyclehist class. I tried the exactly same programme using Python 2.4.1 and Scipy 0.3.2 (based on numeric/numarray) and the result of the "print a+c" didn't get nested as I expect. > > Regards, > Mark > I'm not sure what this is doing -- it looks kind of bizzare -- however, you can fix this case without resorting to subclassing to ndarray. Just toss an '__array_priority__ = 10' up at the top of the class definition and it will use your __methods__ in preference to the ndarrays. I don't have time to look into this further right now unfortunately. -tim > -----Original Message----- > From: numpy-discussion-bounces(a)scipy.org > [mailto:numpy-discussion-bounces@scipy.org] On Behalf Of Stefan van > der Walt > Sent: 18. december 2006 10:36 > To: Discussion of Numerical Python > Subject: Re: [Numpy-discussion] Unexpected output using numpy.ndarray > and__radd__ > > Hi Mark > > On Mon, Dec 18, 2006 at 08:30:20AM +0100, Mark Hoffmann wrote: > >> The following issue has puzzled me for a while. I want to add a >> numpy.ndarray and an instance of my own class. I define this >> operation by implementing the methods __add__ and __radd__. My programme (including output) looks like: >> >> #!/usr/local/bin/python >> >> import numpy >> >> class Cyclehist: >> def __init__(self,vals): >> self.valuearray = numpy.array(vals) >> >> def __str__(self): >> return 'Cyclehist object: valuearray = '+str(self.valuearray) >> >> def __add__(self,other): >> print "__add__ : ",self,other >> return self.valuearray + other >> >> def __radd__(self,other): >> print "__radd__ : ",self,other >> return other + self.valuearray >> >> c = Cyclehist([1.0,-21.2,3.2]) >> a = numpy.array([-1.0,2.2,-2.2]) >> print c + a >> print a + c >> > > In the first instance, c.__add__(a) is called, which works fine. In the second, a.__add__(c) is executed, which is your problem, since you rather want c.__radd__(a) to be executed. A documentation snippets: > > """For instance, to evaluate the expression x-y, where y is an instance of a class that has an __rsub__() method, y.__rsub__(x) is called if x.__sub__(y) returns NotImplemented. > > Note: If the right operand's type is a subclass of the left operand's type and that subclass provides the reflected method for the operation, this method will be called before the left operand's non-reflected method. This behavior allows subclasses to override their ancestors' operations.""" > > Since a.__add__ does not return NotImplemented, c.__radd__ is not called where you expect it to be. I am not sure why broadcasting takes place here, maybe someone else on the list can elaborate. > > To solve your problem, you may want to look into subclassing ndarrays, as described at http://www.scipy.org/Subclasses. > > Cheers > Stéfan > _______________________________________________ > Numpy-discussion mailing list > Numpy-discussion(a)scipy.org > http://projects.scipy.org/mailman/listinfo/numpy-discussion > _______________________________________________ > Numpy-discussion mailing list > Numpy-discussion(a)scipy.org > http://projects.scipy.org/mailman/listinfo/numpy-discussion > > > _______________________________________________ Numpy-discussion mailing list Numpy-discussion(a)scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion

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Re: [Numpy-discussion] Unexpected output using numpy.ndarray and__radd__
by Mark Hoffmann 18 Dec '06

18 Dec '06

I appreciate the answer and the solution suggestion. I see that it is possible to make a work around by subclassing from ndarray. Still, in the "print a+c" statement, I don't understand why a.__add__(c) doesn't return NotImplemented (because ndarray shouldn't recognize the Cyclehist class) and directly call c.__radd__(a) implemented in my Cyclehist class. I tried the exactly same programme using Python 2.4.1 and Scipy 0.3.2 (based on numeric/numarray) and the result of the "print a+c" didn't get nested as I expect. Regards, Mark -----Original Message----- From: numpy-discussion-bounces(a)scipy.org [mailto:numpy-discussion-bounces@scipy.org] On Behalf Of Stefan van der Walt Sent: 18. december 2006 10:36 To: Discussion of Numerical Python Subject: Re: [Numpy-discussion] Unexpected output using numpy.ndarray and__radd__ Hi Mark On Mon, Dec 18, 2006 at 08:30:20AM +0100, Mark Hoffmann wrote: > The following issue has puzzled me for a while. I want to add a > numpy.ndarray and an instance of my own class. I define this operation > by implementing the methods __add__ and __radd__. My programme (including output) looks like: > > #!/usr/local/bin/python > > import numpy > > class Cyclehist: > def __init__(self,vals): > self.valuearray = numpy.array(vals) > > def __str__(self): > return 'Cyclehist object: valuearray = '+str(self.valuearray) > > def __add__(self,other): > print "__add__ : ",self,other > return self.valuearray + other > > def __radd__(self,other): > print "__radd__ : ",self,other > return other + self.valuearray > > c = Cyclehist([1.0,-21.2,3.2]) > a = numpy.array([-1.0,2.2,-2.2]) > print c + a > print a + c In the first instance, c.__add__(a) is called, which works fine. In the second, a.__add__(c) is executed, which is your problem, since you rather want c.__radd__(a) to be executed. A documentation snippets: """For instance, to evaluate the expression x-y, where y is an instance of a class that has an __rsub__() method, y.__rsub__(x) is called if x.__sub__(y) returns NotImplemented. Note: If the right operand's type is a subclass of the left operand's type and that subclass provides the reflected method for the operation, this method will be called before the left operand's non-reflected method. This behavior allows subclasses to override their ancestors' operations.""" Since a.__add__ does not return NotImplemented, c.__radd__ is not called where you expect it to be. I am not sure why broadcasting takes place here, maybe someone else on the list can elaborate. To solve your problem, you may want to look into subclassing ndarrays, as described at http://www.scipy.org/Subclasses. Cheers Stéfan _______________________________________________ Numpy-discussion mailing list Numpy-discussion(a)scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion

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Unexpected output using numpy.ndarray and __radd__
by Mark Hoffmann 18 Dec '06

18 Dec '06

> Hi, > > The following issue has puzzled me for a while. I want to add a > numpy.ndarray and an instance of my own class. I define this operation > by implementing the methods __add__ and __radd__. My programme > (including output) looks like: > > #!/usr/local/bin/python > > import numpy > > class Cyclehist: > def __init__(self,vals): > self.valuearray = numpy.array(vals) > > def __str__(self): > return 'Cyclehist object: valuearray = '+str(self.valuearray) > > def __add__(self,other): > print "__add__ : ",self,other > return self.valuearray + other > > def __radd__(self,other): > print "__radd__ : ",self,other > return other + self.valuearray > > c = Cyclehist([1.0,-21.2,3.2]) > a = numpy.array([-1.0,2.2,-2.2]) > print c + a > print a + c > > # ---------- OUTPUT ---------- > # > # addprob $ addprob.py > # __add__ : Cyclehist object: valuearray = [ 1. -21.2 3.2] [-1. > 2.2 -2.2] > # [ 0. -19. 1.] > # __radd__ : Cyclehist object: valuearray = [ 1. -21.2 3.2] -1.0 > # __radd__ : Cyclehist object: valuearray = [ 1. -21.2 3.2] 2.2 > # __radd__ : Cyclehist object: valuearray = [ 1. -21.2 3.2] -2.2 > # [[ 0. -22.2 2.2] [ 3.2 -19. 5.4] [ -1.2 -23.4 1. ]] > # addprob $ > # > # ---------------------------- > > > I expected the output of "c+a" and "a+c" to be identical, however, the > output of "a+c" gets nested in an elementwise fashion. Can anybody > explain this? Is it a bug or a feature? I'm using Python 2.4.4c1 and > numpy 1.0. I tried the programme using an older version of Python and > numpy and there the result of "c+a" and "a+c" are identical. > > > Regards, > > Mark Hoffmann >

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Anyone have a "little" shooting-method function to share
by David L Goldsmith 17 Dec '06

17 Dec '06

Hi! I tried to send this earlier: it made it into my sent mail folder, but does not appear to have made it to the list. I need to numerically solve: (1-t)x" + x' - x = f(t), x(0) = x0, x(1) = x1 I've been trying to use (because it's the approach I inherited) an elementary finite-difference discretization, but unit tests have shown that that approach isn't working. After a little review, I believe I understand the problem: near t=0, the thing is like an advection-diffusion equation with diffusion as strong as advection (a case I'm sure is treated somewhere in the literature, but not as easily findable as:) near t=1, the thing is like the advection-diffusion equation I did easily find treated, namely one where advection dominates. Based on that treatment, I understand why an FD approach (with a uniform grid) would fail around t=0, and from there it is easy to accept that the fact that the thing changes its "nature" over the course of its "life," implies that (a uniform grid) FD is probably not a very good approach for this equation anywhere on its domain. I could try (and maybe will have to) a variable grid FD approach, but I'd first like to try a "shooting" method (for some reason my intuition is telling me that in this case this might be more efficient). This is where you all come in: I understand the algorithm and could (may have to) code it myself, but if anyone out there already has code for this (in Python using numpy, and preferably already under test), might you be willing to share? Thanks in advance, David Goldsmith PS: In the interim, I realized that if something like this "pre-exists" in a module, that module might be scipy. Sure enough, scipy has integrate.ode and integrate.odeint; Google-ing scipy: integrate.odeint help led me to Travis's 2004 "SciPy Tutorial," where I find "There are many optional inputs and outputs available when using odeint which can help tune the solver. These additional inputs and outputs are not needed much of the time, however..." Well, is one of those inputs an algorithm specifier? Alternatively, is there a "shooting" algorithm implemented elsewhere in scipy? ------------------------------------------------------------------------- Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with pre-integrated technology to make your job easier Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.as-us.falkag.net/sel?cmd=lnk&kid=120709&bid=263057&dat=121642

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Re: [Numpy-discussion] Pyrex and numpy
by Evan Lapisky 15 Dec '06

15 Dec '06

> I was just going to try pyrex out with numpy to see how it compares with > weave (which is cool but quirky). My first attempt ended in failure: I > tried to compile the demo in in numpy/doc/pyrex and got this error: > > c_numpy.pxd:99:22: Array element cannot be a Python object > > > Does anyone who uses pyrex see this? Does anyone know what it's from? > Not that I deleted numpyx.c, since otherwise pyrex isn't invoked at all? > I had the same problem. I don't know why it didn't work, but the pyrex example from http://scipy.org/PerformancePython worked just fine. -Evan

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