NumPy-Discussion December 2003

numpy-discussion@python.org

42 participants
61 discussions

by Michiel Jan Laurens de Hoon

Dear pythoneers, In Chapter 12 ("Writing a C extension") in the Numerical Python manual, in the first example PyArray_ContiguousFromObject is used together with PyDECREF, while in the last example PyArray_ContiguousFromObject is used but the arrays are not PyDECREF'ed before the function returns. From Chapter 13 ("C API Reference") it seems that a PyDECREF is needed in both cases. Or am I missing something here? Is PyDECREF not needed for some reason in the last example? Thanks in advance, Michiel de Hoon U Tokyo First example: ============== static PyObject * trace(PyObject *self, PyObject *args) { PyObject *input; PyArrayObject *array; double sum; int i, n; if (!PyArg_ParseTuple(args, "O", &input)) return NULL; array = (PyArrayObject *) PyArray_ContiguousFromObject(input, PyArray_DOUBLE, 2, 2); if (array == NULL) return NULL; n = array->dimensions[0]; if (n > array->dimensions[1]) n = array->dimensions[1]; sum = 0.; for (i = 0; i < n; i++) sum += *(double *)(array->data + i*array->strides[0] + i*array->strides[1]); Py_DECREF(array); return PyFloat_FromDouble(sum); } Last example: ============= static PyObject * matrix_vector(PyObject *self, PyObject *args) { PyObject *input1, *input2; PyArrayObject *matrix, *vector, *result; int dimensions[1]; double factor[1]; double real_zero[1] = {0.}; long int_one[1] = {1}; long dim0[1], dim1[1]; extern dgemv_(char *trans, long *m, long *n, double *alpha, double *a, long *lda, double *x, long *incx, double *beta, double *Y, long *incy); if (!PyArg_ParseTuple(args, "dOO", factor, &input1, &input2)) return NULL; matrix = (PyArrayObject *) PyArray_ContiguousFromObject(input1, PyArray_DOUBLE, 2, 2); if (matrix == NULL) return NULL; vector = (PyArrayObject *) PyArray_ContiguousFromObject(input2, PyArray_DOUBLE, 1, 1); if (vector == NULL) return NULL; if (matrix->dimensions[1] != vector->dimensions[0]) { PyErr_SetString(PyExc_ValueError, "array dimensions are not compatible"); return NULL; } dimensions[0] = matrix->dimensions[0]; result = (PyArrayObject *)PyArray_FromDims(1, dimensions, PyArray_DOUBLE); if (result == NULL) return NULL; dim0[0] = (long)matrix->dimensions[0]; dim1[0] = (long)matrix->dimensions[1]; dgemv_("T", dim1, dim0, factor, (double *)matrix->data, dim1, (double *)vector->data, int_one, real_zero, (double *)result->data, int_one); return PyArray_Return(result); } -- Michiel de Hoon, Assistant Professor University of Tokyo, Institute of Medical Science Human Genome Center 4-6-1 Shirokane-dai, Minato-ku Tokyo 108-8639 Japan http://bonsai.ims.u-tokyo.ac.jp/~mdehoon

10 years, 6 months

Fw: [Numpy-discussion] numarray.records - get/set item

by Sebastian Haase

My situation where I got onto this, is having one field named 'mmm' ("MinMaxMean") being an 3 element array. Now, to assign the values first I tried: self.hdrArray = makeHdrArray(self.h) #this makes the record array self.hdr = self.hdrArray[0].field #this is my shortcut to the bound member function # it essentially is a solution (hack) for the getitem part # but regarding setitem I had to learn that "assigning to a function" is illigal in Python - as opposed to C++ #so to do assignment I need to do: self.hdr('mmm')[0], self.hdr('mmm')[1], self.hdr('mmm')[2] = (mi,ma,av) now that I'm looking at it, self.hdrArray[0].setfield('mmm', (mi,ma,av)) would probably be better... How about adding an attribute 'f' which could serve as a "proxy" to allow: myRec.f.mmm = (mi,ma,av) and maybe even additionally: myRec.f['mmm'] = (mi,ma,av) Regards, Sebastian ----- Original Message ----- From: "Perry Greenfield" <perry(a)stsci.edu> To: "Sebastian Haase" <haase(a)msg.ucsf.edu>; <numpy-discussion(a)lists.sourceforge.net> Sent: Thursday, December 04, 2003 3:08 PM Subject: RE: [Numpy-discussion] numarray.records - get/set item > > Hi, > > Is it maybe a good idea to add this to the definition of 'class Record' > > > > class Record: > > """Class for one single row.""" > > <snip> > > def __getitem__(self, fieldName): > > return self.array.field(fieldName)[self.row] > > def __setitem__(self, fieldName, value): > > self.array.field(fieldName)[self.row] = value > > > > I don't know about the implications if __delitem __ and so on are not > > defined. > > I just think it would look quite nice to say > > myRecArr[0]['mmm'] = 'hallo' > > as opposed to > > myRecArr[0].setfield('mmm', 'hallo') > > > > Actually I would even like > > myRecArr[0].mmm = 'hallo' > > > > This should be possible by defining __setattr__. > > It would obviously only work for fieldnames that do not contain '.' or ' ' > > or ... > > > > Any comments ? > > > > > We've had many internal discussions about doing this. The latter was > considered a problem because of possible name collisions of field > names with other attributes or methods. The former is not bothered > by this problem, but we decided to be conservative on this and see > how strong the need was. We are interested in other opinions. > > Perry

17 years, 10 months

RE: [Numpy-discussion] Slow conversion from list to arrays

by Nadav Horesh

It works excellent. I see also that there is a corresponding update in the CVS. Happy new (and peaceful) year, Nadav. -----Original Message----- From: Todd Miller [mailto:jmiller@stsci.edu] Sent: Tue 30-Dec-03 16:34 To: Nadav Horesh Cc: numpy-discussion Subject: Re: [Numpy-discussion] Slow conversion from list to arrays On Thu, 2003-12-25 at 03:27, Nadav Horesh wrote: > The conversion for a list of large arrays into a matrix is very slow in > numarray while reasonably fast: > > >>> from numarray import * > >>> a = [arange(200000), arange(200000), arange(200000), arange(200000)] > >>> aa = array(a) # Very slow > > -------------------------------- > > >>> from Numeric import * > >>> a = [arange(200000), arange(200000), arange(200000), arange(200000)] > >>> aa = array(a) # Fast > > Python version: 2.3.3 > numarray version: Official 0.8 > > Tested under WinXP and RH9 linux. > > Any workaround? > Try concatenate. For the array sizes you're looking at, numarray does OK. You may have to adjust the result shape. Todd > Nadav > > > > > > ------------------------------------------------------- > This SF.net email is sponsored by: IBM Linux Tutorials. > Become an expert in LINUX or just sharpen your skills. Sign up for IBM's > Free Linux Tutorials. Learn everything from the bash shell to sys admin. > Click now! http://ads.osdn.com/?ad_id=1278&alloc_id=3371&op=click > _______________________________________________ > Numpy-discussion mailing list > Numpy-discussion(a)lists.sourceforge.net > https://lists.sourceforge.net/lists/listinfo/numpy-discussion -- Todd Miller Space Telescope Science Institute 3700 San Martin Drive Baltimore MD, 21030 (410) 338 - 4576

17 years, 11 months

US STOCK MARKET - MBTT Technology---MERRILL LYNCH On Sector.....gaille

by Harriet Meredith

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17 years, 11 months

Slow conversion from list to arrays

by Nadav Horesh

The conversion for a list of large arrays into a matrix is very slow in numarray while reasonably fast: >>> from numarray import * >>> a = [arange(200000), arange(200000), arange(200000), arange(200000)] >>> aa = array(a) # Very slow -------------------------------- >>> from Numeric import * >>> a = [arange(200000), arange(200000), arange(200000), arange(200000)] >>> aa = array(a) # Fast Python version: 2.3.3 numarray version: Official 0.8 Tested under WinXP and RH9 linux. Any workaround? Nadav

17 years, 11 months

"error getting read buffer data ptr"

by Edward C. Jones

What are the usual causes for this traceback: Traceback (most recent call last): File "/home/edcjones/cvlib/phase03/IM/slide/test03.py", line 166, in ? test4() File "/home/edcjones/cvlib/phase03/IM/slide/test03.py", line 125, in test4 print arrout File "/usr/local/lib/python2.3/site-packages/numarray/numarraycore.py", line 631, in __str__ return array_str(self) File "/usr/local/lib/python2.3/site-packages/numarray/numarraycore.py", line 1159, in array_str return arrayprint.array2string( File "/usr/local/lib/python2.3/site-packages/numarray/arrayprint.py", line 187, in array2string separator, prefix) File "/usr/local/lib/python2.3/site-packages/numarray/arrayprint.py", line 140, in _array2string data = _gen.ravel(a) File "/usr/local/lib/python2.3/site-packages/numarray/generic.py", line 916, in ravel return reshape(array, (array.nelements(),)) File "/usr/local/lib/python2.3/site-packages/numarray/generic.py", line 907, in reshape v = v.view() libnumarray.error: NA_updateDataPtr: error getting read buffer data ptr

17 years, 11 months

[Fwd: Re: [Numpy-discussion] "error getting read buffer data ptr"]

by Todd Miller

This is a response I forgot to reply-all. Edward tracked this problem down to a memory management bug in his C-code. -- Todd Miller Space Telescope Science Institute 3700 San Martin Drive Baltimore MD, 21030 (410) 338 - 4576

17 years, 11 months

US STOCK MARKET - MBTT Technology---MERRILL LYNCH On Sector.....antonie

by Zachariah Kincaid

17 years, 11 months

Linking numarray with ATLAS

by Nadav Horesh

The following recipe worked on RH9 and gentoo 1.4: 1. Set environment variable USE_LAPACK: export USE_LAPACK=1 2. Edit addon.py and make the following changes: 1. Change the first item of lapack_libs from 'blas' to 'atlas' 2. Change lapack_dirs from [] to ['directory of libatlas.a', 'directory of libg2c.a'] 3. Proceed with the usual installation: python setup.py ... I had some problem on the RH9 system that were solved by upgrading to a recent ATLAS package. Enjoy ;) Nadav.

17 years, 11 months

Linking numarray with atlas

by Nadav Horesh

The following recipe worked with RH9 and gentoo linux: 1. Set environment variable USE_LAPACK:

17 years, 11 months

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NumPy-Discussion December 2003