Numeric C extension: bug or error ?

[Philippe Grosse]

Hi,

I don't understand this strange behaviour:

I compile this code :

#include <Python.h>
#include"Numeric/arrayobject.h"

static PyObject *
return_vector(PyObject *self, PyObject *args)
{
PyObject *input1;
PyArrayObject *vector;

if (!PyArg_ParseTuple(args, "O", &input1))
return NULL;

vector = (PyArrayObject
*)PyArray_ContiguousFromObject(input1,PyArray_DOUBLE, 1, 1);

if (vector == NULL)
return NULL;

return PyArray_Return(vector);

}

/* registration table */
static struct PyMethodDef testMethods[] = {
{"return_vector", return_vector, 1}, /* method name, C
funcptr, always-tuple */
{NULL, NULL} /* end of table marker */
};

/* module initializer */
void inittest() /* called on first import */
{ /* name matters if loaded
dynamically */
(void) Py_InitModule("test",testMethods); /* mod name, table ptr */
import_array(); /* indispensable pour utiliser les arrays */
}

Very simple: this module takes a Numeric array (vector) as argument and
send this array back to python...

If I compile it under macOSX, the result in python is:

import test
from Numeric import *
v=array([1.0,2.0,3.0,4.0],Float)
v array([ 1., 2., 3., 4.])
test.return_vector(v)

array([ 1., 2., 3., 4.])

but in linux the result is:

import test
from Numeric import *
v=array([1.0,2.0,3.0,4.0],Float)
v array([ 1., 2., 3., 4.])
test.return_vector(v)

array([ 1.+0.j, 2.+0.j, 3.+0.j, 4.+0.j])

Strange !!! the result is a complex array.
The C vector is really complex because if I try to use it in the C module,
the result is...incomplete.
For example, if I try to multiply each item of the vector array by a
scalar ( pi for example) in a loop, I get this result in python:

import test
from Numeric import *
v=array([1.0,2.0,3.0,4.0],Float)
test.return_vector(v)

array([ 3.14159265+0.j, 0.+0.j, 6.28318531+0.j, 0.+0.j])

It's the result of pi* 1.0, 0.0, 2.0, 0.0 ( the four first elements of the
internal representation of the complex array ([ 1.+0.j, 2.+0.j, 3.+0.j,
4.+0.j]).

Anyone any idea where I'm going wrong?
Thank you for any help.

Philippe

 

[David M. Cooke]

Hi,

I don't understand this strange behaviour:

I compile this code :

[code clipped; it looks good]
....

/* registration table */
static struct PyMethodDef testMethods[] = {
{"return_vector", return_vector, 1}, /* method name, C
funcptr, always-tuple */
{NULL, NULL} /* end of table marker */
};

Instead of the magic constant "1", use METH_VARARGS.

....

Very simple: this module takes a Numeric array (vector) as argument and
send this array back to python...

If I compile it under macOSX, the result in python is:

import test
from Numeric import *
v=array([1.0,2.0,3.0,4.0],Float)
v array([ 1., 2., 3., 4.])
test.return_vector(v)

array([ 1., 2., 3., 4.])

but in linux the result is:

import test
from Numeric import *
v=array([1.0,2.0,3.0,4.0],Float)
v array([ 1., 2., 3., 4.])
test.return_vector(v)

array([ 1.+0.j, 2.+0.j, 3.+0.j, 4.+0.j])

This isn't what I get; I get the same result under linux as you get
from Mac OS X. Have you checked that the copies of the code are the
same?

 

[Philippe Grosse]

Hi,

I don't understand this strange behaviour:

I compile this code :

[code clipped; it looks good]
...

/* registration table */
static struct PyMethodDef testMethods[] = {
{"return_vector", return_vector, 1}, /* method name, C
funcptr, always-tuple */
{NULL, NULL} /* end of table marker */
};

Instead of the magic constant "1", use METH_VARARGS.

I have tried METH_VARARGS: same result

...

Very simple: this module takes a Numeric array (vector) as argument and
send this array back to python...

If I compile it under macOSX, the result in python is:

import test
from Numeric import *
v=array([1.0,2.0,3.0,4.0],Float)
v array([ 1., 2., 3., 4.])
test.return_vector(v)

array([ 1., 2., 3., 4.])

but in linux the result is:

import test
from Numeric import *
v=array([1.0,2.0,3.0,4.0],Float)
v array([ 1., 2., 3., 4.])
test.return_vector(v)

array([ 1.+0.j, 2.+0.j, 3.+0.j, 4.+0.j])

This isn't what I get; I get the same result under linux as you get
from Mac OS X. Have you checked that the copies of the code are the
same?

Yes, I'm sure, the codes are exactly the same.

I use this command to compile under linux:

[grosse@intercalcul dev_fortran]$ gcc -DNDEBUG -O3 -fomit-frame-pointer
-pipe -mcpu=pentiumpro -march=i586 -ffast-math -fno-strength-reduce -fPIC
-g -I/usr/include/python2.2 -c test.c -o test.o

[grosse@intercalcul dev_fortran]$ gcc -shared -g -o test.so test.o

I can understand where is the problem, I'm totaly confused.

Thank you for your help