Mailman 3 April 2005 - NumPy-Discussion

PyArray_ContiguousFromObject & PyDECREF
by Michiel Jan Laurens de Hoon 16 May '11

16 May '11

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

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ANN: numarray-1.2.3
by Todd Miller 10 May '05

10 May '05

numarray-1.2.3 is a bugfix release for numarray-1.2.2 which fixes a problem with universal function setup caching which noticeably impaired 1.2.2 small array performance. Get it if you are new to numarray, haven't upgraded to 1.2.2 yet, or use a lot of small arrays. numarray-1.2.3 is here: http://sourceforge.net/project/showfiles.php?group_id=1369&package_id=32367 Thanks to Ralf Juengling for quietly reporting this and working with me to identify and fix the problem.

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numarray: lexicographical sort
by Edward C. Jones 29 Apr '05

29 Apr '05

Suppose arr is a two dimensional numarray. Can the following be done entirely within numarray? alist = arr.tolist() alist.sort() arr = numarray.array(alist, arr.type())

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numarray: problem with numarray.records
by Edward C. Jones 29 Apr '05

29 Apr '05

#! /usr/bin/env python import numarray, numarray.strings, numarray.records doubles = numarray.array([1.0], 'Float64') strings = numarray.strings.array('abcdefgh', itemsize=8, kind=numarray.strings.RawCharArray) print numarray.records.array(buffer=[strings, strings]) print print numarray.records.array(buffer=[doubles, doubles]) print print numarray.records.array(buffer=[strings, doubles]) """ The output is: RecArray[ ('abcdefgh'), ('abcdefgh') ] RecArray[ (1.0, 1.0) ] Traceback (most recent call last): File "./mess.py", line 12, in ? print numarray.records.array(buffer=[strings, doubles]) File "/usr/local/lib/python2.4/site-packages/numarray/records.py", line 397, in array byteorder=byteorder, aligned=aligned) File "/usr/local/lib/python2.4/site-packages/numarray/records.py", line 106, in fromrecords raise ValueError, "inconsistent data at row %d,field %d" % (row, col) ValueError: inconsistent data at row 1,field 0 The numarray docs (11.2) say: The first argument, buffer, may be any one of the following: ... (5) a list of numarrays. There must be one such numarray for each field. What is going on here? """

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numarray dotblas problem on OSX
by Simon Burton 28 Apr '05

28 Apr '05

Hi, I have a colleague running Mac OS 10.3, running numarray-1.3.1 (from fink) who has managed to bomb on this little code example: >>> import numarray as na >>> import numarray.random_array as ra >>> a = ra.random(shape=(257,256)) >>> b = ra.random(shape=(1,256)) >>> na.innerproduct(a, b) He gets a blas error: ldc must be >= MAX(N,1): ldc=256 N=257Parameter 14 to routine cblas_dgemm was incorrect Mac OS BLAS parameter error in cblas_dgemm, parameter #0, (unavailable), is 0 Simon. -- Simon Burton, B.Sc. Licensed PO Box 8066 ANU Canberra 2601 Australia Ph. 61 02 6249 6940 http://arrowtheory.com

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numarray, Numeric and 64-bit platforms
by Francesc Altet 27 Apr '05

27 Apr '05

Hi, I'm having problems converting numarray objects into Numeric in 64-bit platforms, and I think this is numarray fault, but I'm not completely sure. The problem can be easily visualized in an example (I'm using numarray 1.3.1 and Numeric 24.0b2). In a 32-bit platform (Intel32, Linux): >>> Num=Numeric.array((3,),typecode='l') >>> na=numarray.array(Num,typecode=Num.typecode()) >>> Numeric.array(na,typecode=na.typecode()) array([3],'i') # The conversion has finished correctly In 64-bit platforms (AMD64, Linux): >>> Num=Numeric.array((3,),typecode='l') >>> na=numarray.array(Num,typecode=Num.typecode()) >>> Numeric.array(na,typecode=na.typecode()) Traceback (most recent call last): File "<stdin>", line 1, in ? TypeError: typecode argument must be a valid type. The problem is that, for 32-bit platforms, na.typecode() == 'i' as it should be, but for 64-bit platforms na.typecode() == 'N' that is not a valid type in Numeric. I guess that na.typecode() should be mapped to 'l' in 64-bit platforms so that Numeric can recognize the Int64 correctly. Any suggestion? -- >0,0< Francesc Altet http://www.carabos.com/ V V Cárabos Coop. V. Enjoy Data "-"

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numarray problems on AIX
by Jeff Whitaker 26 Apr '05

26 Apr '05

Hi: I'm having problems with numarray 1.3.1/Python 2.4.1 on AIX 5.2: Python 2.4.1 (#3, Apr 26 2005, 10:34:56) [C] on aix5 Type "help", "copyright", "credits" or "license" for more information. >>> import numarray Traceback (most recent call last): File "<stdin>", line 1, in ? File "/u/wx20wj/home/blue/lib/python2.4/site-packages/numarray/__init__.py", line 42, in ? from numarrayall import * File "/u/wx20wj/home/blue/lib/python2.4/site-packages/numarray/numarrayall.py", line 2, in ? from generic import * File "/u/wx20wj/home/blue/lib/python2.4/site-packages/numarray/generic.py", line 1116, in ? import numarraycore as _nc File "/u/wx20wj/home/blue/lib/python2.4/site-packages/numarray/numarraycore.py", line 1751, in ? import ufunc File "/u/wx20wj/home/blue/lib/python2.4/site-packages/numarray/ufunc.py", line 13, in ? import _converter ImportError: dynamic module does not define init function (init_converter) it works with AIX 4 - anyone seen this before? -Jeff -- Jeffrey S. Whitaker Phone : (303)497-6313 Meteorologist FAX : (303)497-6449 NOAA/OAR/CDC R/CDC1 Email : Jeffrey.S.Whitaker(a)noaa.gov 325 Broadway Office : Skaggs Research Cntr 1D-124 Boulder, CO, USA 80303-3328 Web : http://tinyurl.com/5telg

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Please confirm your request to join IErussian
by Yahoo! Groups 25 Apr '05

25 Apr '05

Hello numpy-discussion(a)lists.sourceforge.net, We have received your request to join the IErussian group hosted by Yahoo! Groups, a free, easy-to-use community service. This request will expire in 7 days. TO BECOME A MEMBER OF THE GROUP: 1) Go to the Yahoo! Groups site by clicking on this link: http://groups.yahoo.com/i?i=anNSKqzsyA7slXUGUdYHvlkpsPI&e=numpy-discussion%… (If clicking doesn't work, "Cut" and "Paste" the line above into your Web browser's address bar.) -OR- 2) REPLY to this email by clicking "Reply" and then "Send" in your email program If you did not request, or do not want, a membership in the IErussian group, please accept our apologies and ignore this message. Regards, Yahoo! Groups Customer Care Your use of Yahoo! Groups is subject to http://docs.yahoo.com/info/terms/

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Value selections?
by Stephen Walton 25 Apr '05

25 Apr '05

I'm trying out Numeric 24b2. In numarray, the following code will plot the values of an array which are not equal to 'flag': f = array!=flag plot(array[f]) What is the equivalent in Numeric 24b2?

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Re: [Numpy-discussion] Numeric 24.0
by Travis Oliphant 21 Apr '05

21 Apr '05

Alexander Schmolck wrote: >Travis Oliphant <oliphant(a)ee.byu.edu> writes: > > > >>I've released Numeric 24.0 as a beta (2nd version) release. Right now it's >>just a tar file. >> >>Please find any bugs. I'll wait a week or two and release a final version >>unless I hear reports of problems. >> >> > > >I suspect some other problems I haven't tried to track down yet are due to >this: > > >>> a = num.array([[1],[2],[3]]) > >>> ~(a==a) > array([[-2], > [-2], > [-2]]) > > What is wrong with this? ~ is bit-wise not and gives the correct answer, here. > >Object array comparisons still produce haphazard behaviour: > > >>> a = num.array(["ab", "cd", "efg"], 'O') > >>> a == 'ab' > 0 > > You are mixing Object arrays and character arrays here and expecting too much. String arrays in Numeric and their relationship with object arrays have never been too useful. You need to be explicit about how 'ab' is going to be interpreted and do a == array('ab','O') to get what you were probably expecting. >Finally -- not necessarily a bug, but a change of behaviour that seems undocumented (I'm >pretty sure this used to give a float array as return value): > > >>> num.zeros((2.0,)) > *** TypeError: an integer is required > > > >'as > > I don't think this worked as you think it did (I looked at Numeric 21.3). num.zeros(2.0) works but it shouldn't. This is a bug that I'll fix. Shapes should be integers, not floats. If this was not checked before than that was a bug. It looks like it's always been checked differently for single-element tuples and scalars So, in short, I see only one small bug here. Thanks for testing things out. -Travis

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