Mailman 3 July 2001 - NumPy-Discussion

simple array help?
by Pete Shinners Sept. 17, 2001

Sept. 17, 2001

i have a simple array with floating values >>> print a array([ 0. , 0.2, 0.4, 0.6, 0.8]) what i need to do is change each index into another dimension with 3 indices. hmm, kind of confusing, an example will explain better >>> b = array(zip(a,a,a)) >>> print b array([[ 0. , 0. , 0. ], [ 0.2, 0.2, 0.2], [ 0.4, 0.4, 0.4], [ 0.6, 0.6, 0.6], [ 0.8, 0.8, 0.8]]) ok, this does the job, but once i start using large arrays, the back-… [View More]

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Help: need info on Fortran/C mixing on Windows
by Paul F. Dubois July 31, 2001

July 31, 2001

Any fellow nummies and Pythonistas out there with experience using Digital Fortran on Windows? I'm trying to get Pyfort to work with Visual Fortran / Visual C++ on Windows. I am not usually a Windows developer so I do not know how to do things like look at an object file to see what names are in it (as I could do with nm on Unix). I have discovered that by including c$DEC ATTRIBUTES C:: foo in my Fortran, where foo is the name of my Fortran function, that my missing external for foo disappears.… [View More]

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RE: [Numpy-developers] Error behavior.
by Paul F. Dubois July 31, 2001

July 31, 2001

Numpys, This is Travis' original message to the developers list, discussing his ideas for dealing with floating point errors. When I answered him a minute ago I inadvertently posted to this list instead. But, it is a good idea to have everyone's thoughts. I only ask that you keep the noise down and not have this degenerate into the numerous IEEE discussions we have had before. Paul P.S. I still am looking for help on solving the Numeric bug on Alphas. -----Original Message----- From: numpy-… [View More]

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RE: [Numpy-developers] Error behavior. (2)
by Paul F. Dubois July 31, 2001

July 31, 2001

I understand why some people might want the behavior (return with inf or NaN etc in arrays rather than get an exception). Let's ask some basic questions. Having done such an operation, how do I tell if I have any errant values in the result? For example, what can I compare x[i] to, in order to know if it is invalid? We have had several requests for full support of IEEE but nobody knows how to do it portably, as far as I know. I resist bringing back fastumath because I wonder if it really … [View More]

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Re: [Numpy-discussion] Troubles with arrays, proposal for Solution
by Phil Austin July 30, 2001

July 30, 2001

Vanroose Wim writes: > Dear Numerical Python Users, > > It is now clear to me, after the comments of Travis Oliphant, > Paul Dubois and Phil Austin, that in EVERY C-file that uses NumPy > extensions, the "import_array" statement must be present. Actually, what I was trying to say (in a message that didn't make it to the list) is the opposite -- import_array must be present in only one file. So below I would do something like: (my additions marked by PA>) &… [View More]gt; > ///////////////////////// > //file: arraytest.h > ////////////////////// > > #include "Python.h" PA> #define PY_ARRAY_UNIQUE_SYMBOL paArray > #include "arrayobject.h" > > double *myTest(void); > > ////////////////////// > // file: arraytest.c > //////////////////// > PA> #define NO_IMPORT_ARRAY > #include "arraytest.h" > > double * myTest(void ){ > double *result; > ... > > return result; > } > > //////////////////// > //file: test.c > //////////////// > #include "arraytest.h" > > static PyObject *function(PyObject *self, PyObject *args){ > > ... > int dimensions[2]; > > dimensions[0] = N; > dimensions[1] = N; > > PyArrayObject *result ; > result = (PyArrayObject *)PyArray_FromDims(2,dimensions,PyArray_DOUBLE); > > double *data; > data = myTest(); > memcpy(result->data,data,N*N*sizeof(double)); > return PyArray_Return(result); > } > > static PyMethodDef testMethods[] = { > {"test",function,1}, > {NULL,NULL} > }; > > extern "C" { > void inittest(){ > PyObject *m,*d; > m = Py_InitModule("test", testMethods); > import_array(); > d = PyModule_GetDict(m); > } > You should see the following when you run /lib/cpp -E on these files: in arraytest.c #define NO_IMPORT_ARRAY #include "arraytest.h" will produce a line like: extern void **paArray; but in test.c #include "arraytest.h" will produce: void **paArray; and import_array(); will expand to { PyObject *numpy = PyImport_ImportModule("_numpy"); if (numpy != 0) { PyObject *module_dict = PyModule_GetDict(numpy); PyObject *c_api_object = PyDict_GetItemString(module_dict, "_ARRAY_API"); if (((c_api_object)->ob_type == &PyCObject_Type)) { paArray = (void **)PyCObject_AsVoidPtr(c_api_object); } } }; The result is that there is a single global function pointer array called paArray that has its space reserved in test.c, and is referenced externally in arraytest.c. This allows you to use any numeric api call in either file. If you compile the module to, say, test.so on unix you should see something like this when you do a nm -D: ~phil% nm -D test.so | grep paArray 000a3d00 B paArray i.e. one instance of paArray in the data segment of the so file. Scanning the output of /lib/cpp -E output is a good way to get a feel for this (on unix anyway). Regards, Phil [View Less]

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Troubles with arrays, proposal for Solution
by Vanroose Wim July 30, 2001

July 30, 2001

Dear Numerical Python Users, It is now clear to me, after the comments of Travis Oliphant, Paul Dubois and Phil Austin, that in EVERY C-file that uses NumPy extensions, the "import_array" statement must be present. However, after some try-outs with parts my code, it seems not a good idea to allow a diffusion of the "import_array" statement and "PyArrayObject" throughout the "C" code. The code becomes unclear by the mixing of Python concepts and C concepts. … [View More]

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Re: Numeric.transpose (incorrect documentation)
by Tim Hochberg July 27, 2001

July 27, 2001

"Curtis Jensen" <cjensen(a)bioeng.ucsd.edu> wrote in message news:3B6076D4.68B6840C@bioeng.ucsd.edu... > the documenation for the "transpose" function for the "Numeric" module > seems to be incoorect, or at least missleading. The correct place for this is probably the numpy-discussion list, so I'm cc'ing it there. Perhaps the Paul Dubois will see it and have some ideas for clearing of the docs. > It says that transpose is suppose to return a "new" array. In fact it > does … [View More]not. It returns a pointer to the same array, only with transposed > indicies. It's been a while since I looked at the NumPy docs, so I don't recall what conventions they use here. However, transpose does return a new array, it just points to the same data as the original. If a=transpose(b), "a is b" is false and "a.shape == b.shape" is false, so clearly they are different objects (i.e., different arrays). You know most of this, as you demonstrate down below, I just wanted to make the point that there is a difference between a new array and new data. Note that nearly every operation that can return a reference rather than a copy does so. Even slicing, if b=a[3:5], then 'b' holds a reference to the same data as 'a'. Some functions go so far to return a reference when they can, but otherwise copy. See ravel for example -- it copies the data if its argument is not contiguous, otherwise it uses a reference. Now _that_ can be confusing! Useful though. -tim > consider the example: > > Python 1.5.2 (#4, Sep 5 2000, 10:29:12) [C] on irix646 > Copyright 1991-1995 Stichting Mathematisch Centrum, Amsterdam > >>> from Numeric import * > >>> foo = zeros([5,10]) > >>> bar = transpose( foo ) > >>> foo > array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], > [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], > [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], > [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], > [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]) > >>> bar > array([[0, 0, 0, 0, 0], > [0, 0, 0, 0, 0], > [0, 0, 0, 0, 0], > [0, 0, 0, 0, 0], > [0, 0, 0, 0, 0], > [0, 0, 0, 0, 0], > [0, 0, 0, 0, 0], > [0, 0, 0, 0, 0], > [0, 0, 0, 0, 0], > [0, 0, 0, 0, 0]]) > >>> foo[0,2] = 1 > >>> foo > array([[0, 0, 1, 0, 0, 0, 0, 0, 0, 0], > [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], > [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], > [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], > [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]) > >>> bar > array([[0, 0, 0, 0, 0], > [0, 0, 0, 0, 0], > [1, 0, 0, 0, 0], > [0, 0, 0, 0, 0], > [0, 0, 0, 0, 0], > [0, 0, 0, 0, 0], > [0, 0, 0, 0, 0], > [0, 0, 0, 0, 0], > [0, 0, 0, 0, 0], > [0, 0, 0, 0, 0]]) > >>> > > > if bar was truely a new array, then changes to foo would not affect > bar. In the example above, it does. This way actualy works better for > my purposes, however, the documentation is missleading. > > -- > Curtis Jensen > cjensen(a)bioeng.ucsd.edu > http://www-bioeng.ucsd.edu/~cjensen/ > FAX (425) 740-1451 [View Less]

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Numpy install problems
by Michael D. Risser July 27, 2001

July 27, 2001

When attempting to install Numeric 17.0 with Python 1.5.2 and Distutils 1.0 on Red Hat 7.0, I get the following error after issuing the command 'python setup.py install' Traceback (innermost last): File "setup.py", line 15, in ? vs = map(string.atoi, v.groups()) AttributeError: 'None' object has no attribute 'groups' This error occurs regardless of whether or not I am root. I have also tried uninstalling the Red Hat Python packages and installing all from source, but I get the same … [View More]

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Troubles with arrays
by Wim Vanroose July 27, 2001

July 27, 2001

Dear Numerical Python Users, I have a small program that produces array's that I want to import in Python. The code is organised in three files. 1) arraytest.h, 2) arraytest.c 3) testmodule.c. and the code is shown below. The function myTest() produces the array and is called from the test module. However, the program does not work! it crashes. In my opinion, I do not have yet enough insight in Numerical Python. Is there an essential part that I do not understand. Remarkable … [View More]

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vec-operator
by Nils Wagner July 26, 2001

July 26, 2001

Hi, A matrix operation is that of stacking the columns of a matrix one under the other to form a single column. This operation is called "vec" or "cs" (c)olumn (s)tring Example A is a m * n matrix vec(A) = reshape(transpose(A),(m*n,1)) How can I copy the result of vec(A) into the i-th column of another matrix called B ? Thanks in advance. Nils

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