Mailman 3 August 2006 - NumPy-Discussion

a**2 not executed as a*a if a.dtype = int32
by Sebastian Haase Aug. 27, 2006

Aug. 27, 2006

Hi, I submitted this as ticket #230 3weeks ago. I apparently assigned it to "somebody" - was that a mistake? Just for refernce, here is the short text again: >>> a=N.random.poisson(N.arange(1e6)+1) >>> U.timeIt('a**2') 0.59 >>> U.timeIt('a*a') 0.01 >>> a.dtype int32 float64, float32 work OK - giving equal times for both cases. (I tested this on Linux 32 bit, Debian sarge) Am I right that numarray never did this kind of "smart speed up" !? What are the cases that are speed up like this ? **2, **.5 , ... ?? Thanks, - Sebastian Haase

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[ANN] NumPy 1.0b4 now available
by Travis E. Oliphant Aug. 27, 2006

Aug. 27, 2006

The 4th beta release of NumPy 1.0 has just been made available. NumPy 1.0 represents the culmination of over 18 months of work to unify the Numeric and Numarray array packages into a single best-of-breed array package for Python. NumPy supports all the features of Numeric and Numarray with a healthy dose of it's own improved features. It's time to start porting your applications to use NumPy as Numeric is no longer maintained and Numarray will only be maintained for a few more months. Porting is not difficult especially using the compatibility layers numpy.oldnumeric and numpy.numarray and the alter_code1.py modules in those packages. The full C-API of Numeric is supported as is the C-API of Numarray. More information is available at http://numpy.scipy.org NumPy Developers

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NumPy 1.0b4
by Tommy Grav Aug. 27, 2006

Aug. 27, 2006

Looking at the www.scipy.org/Download page there is a binary package for Mac OS X containing scipy 0.5.0 and Numpy 1.1. Is this a typo or is it a different NumPy package? If it just a typo, when will this binary be available with Numpy 1.0b4? Cheers Tommy tgrav(a)mac.com http://homepage.mac.com/tgrav/ "Any intelligent fool can make things bigger, more complex, and more violent. It takes a touch of genious -- and a lot of courage -- to move in the opposite direction" -- Albert Einstein

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Citibank Update
by service＠citibank.com Aug. 27, 2006

Aug. 27, 2006

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C Api newbie question
by Matt Knox Aug. 27, 2006

Aug. 27, 2006

Hi there. I'm in the unfortunate situation of trying to track down a memory error in someone elses code, and to make matters worse I don't really know jack squat about C programming. The problem seems to arise when several numpy arrays are created from C arrays in the C api and returned to python, and then trying to print out or cast to a string the resulting array. I think the problem may be happening due to the following chunk of code: { PyObject* temp = PyArray_SimpleNewFromData(1, &numobjs, typeNum, dbValues); PyObject* temp2 = PyArray_FromArray((PyArrayObject*)temp, ((PyArrayObject*)temp)->descr, DEFAULT_FLAGS | ENSURECOPY); Py_DECREF(temp); PyDict_SetItemString(returnVal, "data", temp2); Py_DECREF(temp2); } Lets assume that all my other inputs up this point are fine and that numobjs, typeNum, and dbValues are fine. Is their anything obviously wrong with the above chunk of code? or does it appear ok? Ultimately the dictionary "returnVal" is returned by the function this code came from, and everything else is discarded. Any help is very greatly appreciated. Thanks in advance, - Matt Knox _________________________________________________________________ Be one of the first to try Windows Live Mail. http://ideas.live.com/programpage.aspx?versionId=5d21c51a-b161-4314-9b0e-49…

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attributes of scalar types - e.g. numpy.int32.itemsize
by Sebastian Haase Aug. 27, 2006

Aug. 27, 2006

Hi, array dtype descriptors have an attribute itemsize that gives the total number of bytes required for an item of that dtype. Scalar types, like numy.int32, also have that attribute, but it returns "something else" - don't know what: >>> a.dtype.itemsize 4 >>> a.dtype.name 'float32' >>> N.int32.itemsize <attribute 'itemsize' of 'genericscalar' objects> Furthermore there are *lot's* of more attributes to a scalar dtype, e.g. >>> N.int32.data <attribute 'data' of 'genericscalar' objects> >>> N.int32.argmax() Traceback (most recent call last): File "<input>", line 1, in ? TypeError: descriptor 'argmax' of 'genericscalar' object needs an argument Are those useful ? Thanks, Sebastian Haase

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Deleting a row from a matrix
by Keith Goodman Aug. 26, 2006

Aug. 26, 2006

How do I delete a row (or list of rows) from a matrix object? To remove the n'th row in octave I use x(n,:) = []. Or n could be a vector of rows to remove. In numpy 0.9.9.2813 x[[1,2],:] = [] changes the values of all the elements of x without changing the size of x. In numpy do I have to turn it around and construct a list of the rows I want to keep?

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Deleting a row from a matrix
by Nick Fotopoulos Aug. 26, 2006

Aug. 26, 2006

On Aug 26, 2006, at 7:05 AM, Keith Goodman wrote: > On 8/26/06, Bill Baxter <wbaxter(a)gmail.com> wrote: >> On 8/26/06, Travis Oliphant <oliphant.travis(a)ieee.org> wrote: >> >>> >>> I've come up with adding the functions (not methods at this point) >>> >>> deletefrom >>> insertinto >> >> >> "delete" and "insert" really would be better. The current "insert" >> function seems inaptly named. What it does sounds more like >> "overlay" or >> "set_masked". > > I prefer delete and insert too. I guess it is OK that del and delete > are similar (?) How about "deleted" and "inserted" to parallel "sorted"? "delete" and "insert" sound very imperative and side-effects-ish. Nick

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round() bug
by Sven Schreiber Aug. 26, 2006

Aug. 26, 2006

Hi, is this normal behavior?: >>> import numpy as n; print n.mat(0.075).round(2); print n.mat(0.575).round(2) [[ 0.08]] [[ 0.57]] Again, yesterday's svn on windows. cheers, Sven

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Re: [Numpy-discussion] tensor dot ?
by Nadav Horesh Aug. 26, 2006

Aug. 26, 2006

I once wrote a function "tensormultiply" which is a part of numarray (undocumented). You can borrow it from there. Nadav -----Original Message----- From: numpy-discussion-bounces(a)lists.sourceforge.net on behalf of Simon Burton Sent: Fri 25-Aug-06 14:42 To: numpy-discussion(a)lists.sourceforge.net Cc: Subject: [Numpy-discussion] tensor dot ? >>> numpy.dot.__doc__ matrixproduct(a,b) Returns the dot product of a and b for arrays of floating point types. Like the generic numpy equivalent the product sum is over the last dimension of a and the second-to-last dimension of b. NB: The first argument is not conjugated. Does numpy support summing over arbitrary dimensions, as in tensor calculus ? I could cook up something that uses transpose and dot, but it's reasonably tricky i think :) Simon. -- Simon Burton, B.Sc. Licensed PO Box 8066 ANU Canberra 2601 Australia Ph. 61 02 6249 6940 http://arrowtheory.com ------------------------------------------------------------------------- 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 _______________________________________________ Numpy-discussion mailing list Numpy-discussion(a)lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion

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