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#include "cos_doubles.h"

#include <math.h>

/*  Compute the cosine of each element in in_array, storing the result in

*  out_array. */

void cos_doubles(double * in_array, double * out_array, int size){

int i;

for(i=0;i<size;i++){

out_array[i] = cos(in_array[i]);

}

}

#ifndef _COS_DOUBLES_H

#define _COS_DOUBLES_H

void cos_doubles(double * in_array, double * out_array, int size);

#endif

""" Example of wrapping a C function that takes C double arrays as input using

the Numpy declarations from Cython """

# import both numpy and the Cython declarations for numpy

import numpy as np

cimport numpy as np

# if you want to use the Numpy-C-API from Cython

# (not strictly necessary for this example)

np.import_array()

# cdefine the signature of our c function

cdef extern from "cos_doubles.h":

void cos_doubles (double * in_array, double * out_array, int size)

# create the wrapper code, with numpy type annotations

def cos_doubles_func(np.ndarray[double, ndim=1, mode="c"] in_array not None,

np.ndarray[double, ndim=1, mode="c"] out_array not None):

cos_doubles(<double*> np.PyArray_DATA(in_array),

<double*> np.PyArray_DATA(out_array),

in_array.shape[0])

from distutils.core import setup, Extensionimport numpyfrom Cython.Distutils import build_ext

setup(

cmdclass={'build_ext': build_ext},

ext_modules=[Extension("cos_doubles",

sources=["_cos_doubles.pyx", "cos_doubles.c"],

include_dirs=[numpy.get_include()])],

)

# file: test.py

import cos_doubles

import numpy as np

import matplotlib.pyplot as plt

a = np.linspace(-5, 5, 100)

b = np.empty_like(a)

cos_doubles.cos_doubles_func(a, b)

plt.plot(b)

plt.show

()