NumPy-Discussion November 2000

numpy-discussion@python.org

15 participants
16 discussions

Trouble with extension using NumPy on the Mac
by Chris Barker 23 Nov '00

23 Nov '00

Hi all, I'm cross posting this to the NumPy List and the MacPython list, because it involves NumPy on the Mac, so I'm not sure which group can be most helpfull. It took me a while to get this far, and I finally got everything to compile, but now I have a crashing problem. It seems to be a problem with PyArray_Type not being seen as a PyObject. I am pretty new to C, but I have consulted with a number of folks I work with that know a lot more than I do, and this seems to be a pretty esoteric C issue. It also seems to be compiler dependent, because I have all this working fine on Linux with gcc. I have chopped my problem down into a very small function that demonstrates the problem. The function takes a contiguous NumPy array of Floats (doubles) and multiplies every element by two (in place), and returns None. Here is the code as it works on Linux: #include "Python.h" #include "arrayobject.h" /* A function that doubles an array of Floats in place*/ static PyObject * minimal_doublearray(PyObject *self, PyObject *args) { PyArrayObject *array; int i, num_elements; double *data_array ; if (!PyArg_ParseTuple(args, "O!", &PyArray_Type, &array)) return NULL; if (array->descr->type_num != PyArray_DOUBLE) { PyErr_SetString(PyExc_ValueError, "array must be of type Float"); return NULL; } data_array = (double *) array->data; /*num_elements = PyArray_Size((PyObject *) array);*/ num_elements = PyArray_Size(array); printf("The size of the array is: %i elements\n",num_elements); for (i= 0; i < num_elements; i++) data_array[i] = 2 * data_array[i]; return Py_None; } static PyMethodDef minimalMethods[] = { {"doublearray", minimal_doublearray, METH_VARARGS}, {NULL, NULL} /* Sentinel */ }; void initminimal() { (void) Py_InitModule("minimal", minimalMethods); } Note that the call to: "PyArray_Size(array)" gives me a "./minimal.c:28: warning: passing arg 1 from incompatible pointer type " on gcc on linux. In CodeWarrior on the Mac, it is an fatal error. With the typcast (see previous commented out line) it gives no warnings, and compiles on both systems. Here is a small script to test it: #!/usr/bin/env python from Numeric import * import minimal print "\nTesting doublearray" a = arange(10.0) print a minimal.doublearray(a) print a print "the second version should be doubled" This works fine on Linux, and gives the appropriate errors if the wrong type object is passed in. On the Mac, it crashes. Trying various things, I found that it crashes on the if (!PyArg_ParseTuple(args, "O!", &PyArray_Type, &array)) return NULL; line. If I use: if (!PyArg_ParseTuple(args, "O", &array)) return NULL; It works. Then it crashes on the: num_elements = PyArray_Size((PyObject *) array); line. If I use another way to determine the number of elements, like: num_elements = 1; for (i=0,i<array->nd,i++) num_elements = num_elements * array->dimensions[1]; Then I can get it to work. What is going on? anyone have any suggestions? MacPython 1.5.2c The NumPy that came with MacPython 1.5.2c CodeWarrior pro 5. Thanks for any suggestions, -Chris -- Christopher Barker, Ph.D. cbarker(a)jps.net --- --- --- http://www.jps.net/cbarker -----@@ -----@@ -----@@ ------@@@ ------@@@ ------@@@ Water Resources Engineering ------ @ ------ @ ------ @ Coastal and Fluvial Hydrodynamics ------- --------- -------- ------------------------------------------------------------------------ ------------------------------------------------------------------------

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(no subject)
by Anderl 20 Nov '00

20 Nov '00

Hello, I'm quite new to numpy, trying to migrate from IDL. I'm not able to find any 'shift' function in numpy, i.e. a function that shifts the content of an array by a certain number of elements. a = [1,2,3,4,5,6] shift(a,2) = [3,4,5,6,1,2] In IDL this works even on multidemiensional arrays, b=shift(a,4,7,5) shifts by 4 in the first, 7 in the second and 5 in the third component. Is there some similar module existing? Thanks & best regards, Andreas ------------------------------------------------------------------- Andreas Reigber Institut fuer Hochfrequenztechnik DLR - Oberpfaffenhofen Tel. : ++49-8153-282367 Postfach 1116 eMail: Andreas.Reigber(a)dlr.de D-82230 Wessling -------------------------------------------------------------------

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Fatal Python error: Unprotected floating point exception
by Jean-Bernard Addor 18 Nov '00

18 Nov '00

Hi Numpy people! My nice numpy code generates very few Inf numbers, wich destroy the results of my longer simulations. I was dreaming to have the processor raising an interruption and python caching it to locate and understand quickly why and how it is happening and correct the code. I currently use Python 1.5.2 with Numeric 11 on debian linux 2 . I made some very desappointing test with the module fpectl The last result I got is: Fatal Python error: Unprotected floating point exception Abort Do I have to understand that my Numpy is not compatible with fpectl? Any idea if a more up to date Numpy would be compatible? I find no info on: http://sourceforge.net/projects/numpy Thanks for your help. Jean-Bernard

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bilinear/sampled scaling
by Pete Shinners 08 Nov '00

08 Nov '00

i have image data in a 2D array that i'd like to change the size of. currently, i'm just doing a dirty sampled scaling that i came up with. this works, but can only do a 2x resize. dst[::2,::2] = src dst[1::2,::2] = src dst[:,1::2] = dst[:,::2] this isn't too bad, but it's definitely one of my bottlenecks, can the code to do this be sped through some ingenious use of numeric? i'm also trying to figure out a clean, fast way to do bilinear scaling on my data. it seems like there would be something in numeric to do linear resampling, but i haven't figured it out. i'd like to be able to resample stuff like audio data as well as just image data. thanks for any pointers into this.

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performance of real_fft with fftpacklite.c
by Bernd Rinn 03 Nov '00

03 Nov '00

Hello, does anyone know why the performance of FFT.real with fftpacklite.c is so unballanced for n=2**i and different values of i? My example is: ======================================================================= from Numeric import array,Float from FFT import real_fft from time import time i=1 while i<20: n = 2**long(i) a=array(range(long(1),n),Float) anfang = time() b = real_fft(a) ende=time() print "i=", i, " time: ", ende-anfang i+=1 ======================================================================= and the result shows (on a Pentium-III-700 under Linux): ================================================================= i= 1 time: 0.000182032585144 i= 2 time: 0.000133991241455 i= 3 time: 0.00012195110321 i= 4 time: 0.000123977661133 i= 5 time: 0.000131964683533 i= 6 time: 0.000155925750732 i= 7 time: 0.000362992286682 i= 8 time: 0.000240921974182 i= 9 time: 0.000506043434143 i= 10 time: 0.00064492225647 i= 11 time: 0.00177395343781 i= 12 time: 0.0025269985199 i= 13 time: 0.886229038239 i= 14 time: 0.0219050645828 i= 15 time: 0.0808279514313 i= 16 time: 0.327404975891 i= 17 time: 482.979220986 i= 18 time: 0.803207993507 i= 19 time: 7782.23972797 ================================================================= when I am using an array a of length 2**19 and giving the command b=real_fft(a,n=2**long(20)) the time drops from over two hours CPU-time to about 1.5 seconds. I know that fftpacklite.c is not specially optimized, but isn't a FFT method with vectors lenghts that are powers of 2 be supposed to show a more predictible run-time behavior? Could perhaps anyone point me to a free FFTPACK FORTRAN package for Linux with g77 that performs better than the default package? Any hint would be greatly appreciated. Best regards, Bernd Rinn P.S.: Please CC to Bernd.Rinn(a)uni-konstanz.de since I am not a member of the list. -- Bernd Rinn Fakultät für Physik Universität Konstanz Tel. 07531/88-3812, e-mail: Bernd.Rinn(a)uni-konstanz.de PGP-Fingerprint: 1F AC 31 64 FF EF A9 67 6E 0D 4C 26 0B E7 ED 5C

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Static linking with Python 2.0 (Setup.local)
by Sam Tannous 03 Nov '00

03 Nov '00

I successfully installed the latest release with the distutils package. But now I need to statically link the Numeric package into my Python 2.0 interpreter (it's easier for me to ship "frozen" python binaries for some lab machines...one file instead of hundreds). Could anyone please email me (or post) the section of your Modules/Setup.local that can do this? Something like: _numpy _numpymodule.c -L/users/stannous/lib -L/usr/lib -lm -I/users/stannous/include just doesn't work... TIA, Sam

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NumPy-Discussion November 2000