matlab 2012 vs2010混合编程

电脑配置：

操作系统：window 8.1

Matlab 2012a安装路径：D:\Program Files\MATLAB\R2012a

VS2010 :

OpenCV 2.4.3：D:\Program Files\opencv

补充说明：

在配置前，先检查一下系统变量：

1.若缺少系统变量(该路径必须添加！！！)：

D:\Program Files\MATLAB\R2012a\runtime\win64

导致结果：程序无法正常启动0x000007b。请单击“确定”关闭应用程序

注意变量配置后记得重启才会生效，而且添加路径要在英文符号下加入” ; ”,末尾不需要加分号！！！！

2.其他变量：可加可不加，经验证不会影响结果！！！

(1)用户变量：

D:\Program Files\MATLAB\R2012a\bin\win64

D:\Program Files\MATLAB\R2012a\runtime\win64

(2)系统变量：

D:\Program Files\MATLAB\R2012a\bin\win64

本文转自博客：http://www.cnblogs.com/newpanderking/articles/4057977.html

1、背景

众所周知，matlab在处理矩阵、数学计算、计算机仿真、图像处理等方面有着 c c++无可比拟的优势，但是做成系统供使用时，又显得过于粗糙，为了使用起来高大上，计算起来有简单，方便。无疑，c++ 与matlab混合编程将会使非常靠谱的选择。

这里暂且不论所谓的matlab效率低，c/c++效率高的问题，自我感觉，以我目前编码的功底，所编写的代码的效率远远不及matlab提供的代码的效率。除非你是大牛，或者你是人云亦云，所以能用matlab混合c++编码还是很不错的选择，话不多说，我们开始讨论正题。

2、我使用的版本是matlab2012与vs2010混合编程的。

软件的下载这里就不多说了，我相信看这篇教程的你，这两个软件已经安装的妥妥当当的了。

这里我选用网上常用来做例子的matlab代码做测试，spline.m,该文件位于

D:\Program Files\MATLAB\R2012a\toolbox\matlab\polyfun

当然该文件中依赖调用另一个文件chckxy.m，该文件也在这条路径下。找到后复制到matlab的工作目录下。

这里为了方便提供两个文件的代码：

spline.m

 1 function output = spline(x,y,xx)
 2 %SPLINE Cubic spline data interpolation.
 3 %   PP = SPLINE(X,Y) provides the piecewise polynomial form of the
 4 %   cubic spline interpolant to the data values Y at the data sites X,
 5 %   for use with the evaluator PPVAL and the spline utility UNMKPP.
 6 %   X must be a vector.
 7 %   If Y is a vector, then Y(j) is taken as the value to be matched at X(j),
 8 %   hence Y must be of the same length as X  -- see below for an exception
 9 %   to this.
10 %   If Y is a matrix or ND array, then Y(:,...,:,j) is taken as the value to
11 %   be matched at X(j),  hence the last dimension of Y must equal length(X) --
12 %   see below for an exception to this.
13 %
14 %   YY = SPLINE(X,Y,XX) is the same as  YY = PPVAL(SPLINE(X,Y),XX), thus
15 %   providing, in YY, the values of the interpolant at XX.  For information
16 %   regarding the size of YY see PPVAL.
17 %
18 %   Ordinarily, the not-a-knot end conditions are used. However, if Y contains
19 %   two more values than X has entries, then the first and last value in Y are
20 %   used as the endslopes for the cubic spline.  If Y is a vector, this
21 %   means:
22 %       f(X) = Y(2:end-1),  Df(min(X))=Y(1),    Df(max(X))=Y(end).
23 %   If Y is a matrix or N-D array with SIZE(Y,N) equal to LENGTH(X)+2, then
24 %   f(X(j)) matches the value Y(:,...,:,j+1) for j=1:LENGTH(X), then
25 %   Df(min(X)) matches Y(:,:,...:,1) and Df(max(X)) matches Y(:,:,...:,end).
26 %
27 %   Example:
28 %   This generates a sine-like spline curve and samples it over a finer mesh:
29 %       x = 0:10;  y = sin(x);
30 %       xx = 0:.25:10;
31 %       yy = spline(x,y,xx);
32 %       plot(x,y,‘o‘,xx,yy)
33 %
34 %   Example:
35 %   This illustrates the use of clamped or complete spline interpolation where
36 %   end slopes are prescribed. In this example, zero slopes at the ends of an
37 %   interpolant to the values of a certain distribution are enforced:
38 %      x = -4:4; y = [0 .15 1.12 2.36 2.36 1.46 .49 .06 0];
39 %      cs = spline(x,[0 y 0]);
40 %      xx = linspace(-4,4,101);
41 %      plot(x,y,‘o‘,xx,ppval(cs,xx),‘-‘);
42 %
43 %   Class support for inputs x, y, xx:
44 %      float: double, single
45 %
46 %   See also INTERP1, PCHIP, PPVAL, MKPP, UNMKPP.
47
48 %   Carl de Boor 7-2-86
49 %   Copyright 1984-2010 The MathWorks, Inc.
50 %   $Revision: 5.18.4.6 $  $Date: 2010/09/02 13:36:29 $
51
52
53 % Check that data are acceptable and, if not, try to adjust them appropriately
54 [x,y,sizey,endslopes] = mychckxy(x,y);
55 n = length(x); yd = prod(sizey);
56
57 % Generate the cubic spline interpolant in ppform
58
59 dd = ones(yd,1); dx = diff(x); divdif = diff(y,[],2)./dx(dd,:);
60 if n==2
61    if isempty(endslopes) % the interpolant is a straight line
62       pp=mkpp(x,[divdif y(:,1)],sizey);
63    else         % the interpolant is the cubic Hermite polynomial
64       pp = pwch(x,y,endslopes,dx,divdif); pp.dim = sizey;
65    end
66 elseif n==3&&isempty(endslopes) % the interpolant is a parabola
67    y(:,2:3)=divdif;
68    y(:,3)=diff(divdif‘)‘/(x(3)-x(1));
69    y(:,2)=y(:,2)-y(:,3)*dx(1);
70    pp = mkpp(x([1,3]),y(:,[3 2 1]),sizey);
71 else % set up the sparse, tridiagonal, linear system b = ?*c for the slopes
72    b=zeros(yd,n);
73    b(:,2:n-1)=3*(dx(dd,2:n-1).*divdif(:,1:n-2)+dx(dd,1:n-2).*divdif(:,2:n-1));
74    if isempty(endslopes)
75       x31=x(3)-x(1);xn=x(n)-x(n-2);
76       b(:,1)=((dx(1)+2*x31)*dx(2)*divdif(:,1)+dx(1)^2*divdif(:,2))/x31;
77       b(:,n)=...
78       (dx(n-1)^2*divdif(:,n-2)+(2*xn+dx(n-1))*dx(n-2)*divdif(:,n-1))/xn;
79    else
80       x31 = 0; xn = 0; b(:,[1 n]) = dx(dd,[2 n-2]).*endslopes;
81    end
82    dxt = dx(:);
83    c = spdiags([ [x31;dxt(1:n-2);0] ...
84         [dxt(2);2*(dxt(2:n-1)+dxt(1:n-2));dxt(n-2)] ...
85         [0;dxt(2:n-1);xn] ],[-1 0 1],n,n);
86
87    % sparse linear equation solution for the slopes
88    mmdflag = spparms(‘autommd‘);
89    spparms(‘autommd‘,0);
90    s=b/c;
91    spparms(‘autommd‘,mmdflag);
92
93    % construct piecewise cubic Hermite interpolant
94    % to values and computed slopes
95    pp = pwch(x,y,s,dx,divdif); pp.dim = sizey;
96
97 end
98
99 if nargin==2, output = pp; else output = ppval(pp,xx); end

chckxy.m

  1 function [x,y,sizey,endslopes] = mychckxy(x,y)
  2 %CHCKXY check and adjust input for SPLINE and PCHIP
  3 %   [X,Y,SIZEY] = CHCKXY(X,Y) checks the data sites X and corresponding data
  4 %   values Y, making certain that there are exactly as many sites as values,
  5 %   that no two data sites are the same, removing any data points that involve
  6 %   NaNs, reordering the sites if necessary to ensure that X is a strictly
  7 %   increasing row vector and reordering the data values correspondingly,
  8 %   and reshaping Y if necessary to make sure that it is a matrix, with Y(:,j)
  9 %   the data value corresponding to the data site X(j), and with SIZEY the
 10 %   actual dimensions of the given values.
 11 %   This call to CHCKXY is suitable for PCHIP.
 12 %
 13 %   [X,Y,SIZEY,ENDSLOPES] = CHCKXY(X,Y) also considers the possibility that
 14 %   there are two more data values than there are data sites.
 15 %   If there are, then the first and the last data value are removed from Y
 16 %   and returned separately as ENDSLOPES. Otherwise, an empty ENDSLOPES is
 17 %   returned.  This call to CHCKXY is suitable for SPLINE.
 18 %
 19 %   See also PCHIP, SPLINE.
 20
 21 %   Copyright 1984-2011 The MathWorks, Inc.
 22
 23 % make sure X is a vector:
 24 if length(find(size(x)>1))>1
 25   error(message(‘MATLAB:chckxy:XNotVector‘))
 26 end
 27
 28 % ensure X is real
 29 if any(~isreal(x))
 30   error(message(‘MATLAB:chckxy:XComplex‘))
 31 end
 32
 33 % deal with NaN‘s among the sites:
 34 nanx = find(isnan(x));
 35 if ~isempty(nanx)
 36    x(nanx) = [];
 37    warning(message(‘MATLAB:chckxy:nan‘))
 38 end
 39
 40 n=length(x);
 41 if n<2
 42   error(message(‘MATLAB:chckxy:NotEnoughPts‘))
 43 end
 44
 45 % re-sort, if needed, to ensure strictly increasing site sequence:
 46 x=x(:).‘;
 47 dx = diff(x);
 48
 49 if any(dx<0), [x,ind] = sort(x); dx = diff(x); else ind=1:n; end
 50
 51 if ~all(dx), error(message(‘MATLAB:chckxy:RepeatedSites‘)), end
 52
 53 % if Y is ND, reshape it to a matrix by combining all dimensions but the last:
 54 sizey = size(y);
 55
 56
 57 while length(sizey)>2&&sizey(end)==1, sizey(end) = []; end
 58
 59
 60 yn = sizey(end);
 61 sizey(end)=[];
 62 yd = prod(sizey);
 63
 64 if length(sizey)>1
 65    y = reshape(y,yd,yn);
 66 else
 67    % if Y happens to be a column matrix, change it to the expected row matrix.
 68    if yn==1
 69        yn = yd;
 70        y = reshape(y,1,yn);
 71        yd = 1;
 72        sizey = yd;
 73    end
 74 end
 75
 76 % determine whether not-a-knot or clamped end conditions are to be used:
 77 nstart = n+length(nanx);
 78 if yn==nstart
 79    endslopes = [];
 80 elseif nargout==4&&yn==nstart+2
 81    endslopes = y(:,[1 n+2]); y(:,[1 n+2])=[];
 82    if any(isnan(endslopes))
 83       error(message(‘MATLAB:chckxy:EndslopeNaN‘))
 84    end
 85    if any(isinf(endslopes))
 86        error(message(‘MATLAB:chckxy:EndslopeInf‘))
 87    end
 88 else
 89    error(message(‘MATLAB:chckxy:NumSitesMismatchValues‘,nstart, yn))
 90 end
 91
 92 % deal with NaN‘s among the values:
 93 if ~isempty(nanx)
 94     y(:,nanx) = [];
 95 end
 96
 97 y=y(:,ind);
 98 nany = find(sum(isnan(y),1));
 99 if ~isempty(nany)
100    y(:,nany) = []; x(nany) = [];
101    warning(message(‘MATLAB:chckxy:IgnoreNaN‘))
102    n = length(x);
103    if n<2
104      error(message(‘MATLAB:chckxy:NotEnoughPts‘))
105    end
106 end

function [x,y,sizey,endslopes] = mychckxy(x,y)
%CHCKXY check and adjust input for SPLINE and PCHIP
%   [X,Y,SIZEY] = CHCKXY(X,Y) checks the data sites X and corresponding data
%   values Y, making certain that there are exactly as many sites as values,
%   that no two data sites are the same, removing any data points that involve
%   NaNs, reordering the sites if necessary to ensure that X is a strictly
%   increasing row vector and reordering the data values correspondingly,
%   and reshaping Y if necessary to make sure that it is a matrix, with Y(:,j)
%   the data value corresponding to the data site X(j), and with SIZEY the
%   actual dimensions of the given values.
%   This call to CHCKXY is suitable for PCHIP.
%
%   [X,Y,SIZEY,ENDSLOPES] = CHCKXY(X,Y) also considers the possibility that
%   there are two more data values than there are data sites.
%   If there are, then the first and the last data value are removed from Y
%   and returned separately as ENDSLOPES. Otherwise, an empty ENDSLOPES is
%   returned.  This call to CHCKXY is suitable for SPLINE.
%
%   See also PCHIP, SPLINE.

%   Copyright 1984-2011 The MathWorks, Inc.

% make sure X is a vector:
if length(find(size(x)>1))>1
  error(message(‘MATLAB:chckxy:XNotVector‘))
end

% ensure X is real
if any(~isreal(x))
  error(message(‘MATLAB:chckxy:XComplex‘))
end

% deal with NaN‘s among the sites:
nanx = find(isnan(x));
if ~isempty(nanx)
   x(nanx) = [];
   warning(message(‘MATLAB:chckxy:nan‘))
end

n=length(x);
if n<2
  error(message(‘MATLAB:chckxy:NotEnoughPts‘))
end

% re-sort, if needed, to ensure strictly increasing site sequence:
x=x(:).‘;
dx = diff(x);

if any(dx<0), [x,ind] = sort(x); dx = diff(x); else ind=1:n; end

if ~all(dx), error(message(‘MATLAB:chckxy:RepeatedSites‘)), end

% if Y is ND, reshape it to a matrix by combining all dimensions but the last:
sizey = size(y);

while length(sizey)>2&&sizey(end)==1, sizey(end) = []; end

yn = sizey(end);
sizey(end)=[];
yd = prod(sizey);

if length(sizey)>1
   y = reshape(y,yd,yn);
else
   % if Y happens to be a column matrix, change it to the expected row matrix.
   if yn==1
       yn = yd;
       y = reshape(y,1,yn);
       yd = 1;
       sizey = yd;
   end
end

% determine whether not-a-knot or clamped end conditions are to be used:
nstart = n+length(nanx);
if yn==nstart
   endslopes = [];
elseif nargout==4&&yn==nstart+2
   endslopes = y(:,[1 n+2]); y(:,[1 n+2])=[];
   if any(isnan(endslopes))
      error(message(‘MATLAB:chckxy:EndslopeNaN‘))
   end
   if any(isinf(endslopes))
       error(message(‘MATLAB:chckxy:EndslopeInf‘))
   end
else
   error(message(‘MATLAB:chckxy:NumSitesMismatchValues‘,nstart, yn))
end

% deal with NaN‘s among the values:
if ~isempty(nanx)
    y(:,nanx) = [];
end

y=y(:,ind);
nany = find(sum(isnan(y),1));
if ~isempty(nany)
   y(:,nany) = []; x(nany) = [];
   warning(message(‘MATLAB:chckxy:IgnoreNaN‘))
   n = length(x);
   if n<2
     error(message(‘MATLAB:chckxy:NotEnoughPts‘))
   end
end

ps:说明下，由于这两个文件都是matlab的工具文件，所以chckxy.m在调用时，改了名字叫做mychckxy.m，相应的文件名字也需要改。

做一个简单的测试，做一个调用：

clc;
clear all;
close all;
x = 0:10;
y = sin(x);
xx = 0:.25:10;
yy = spline(x,y,xx)
plot(x,y,‘o‘,xx,yy);

运行结果：

到此为止，都是准备工作做，下面开始介绍如何在vs中调用spline函数。

1）在matlab中输入命令 mbuild -setup , 运行结果如下图所示, 按照提示选择编译器 vs2010.

mbuild -setup

然后键入：mex -setup 命令，运行结果如下图所示,按照提示选择编译器 vs2010

mex -setup

然后在matlab命令窗口输入：

 mcc -W cpplib:libspline -T link:lib spline.m

spline是名字，会根据.m文件的不同而不同！！！

或者输入：mcc -B csharedlib:name name.m

可以得到如下图这些文件：

依然，其中的"libspline.dll"、"libspline.h"和"libspline.lib"这三个文件是我们所需的。

2）打开vs2010建一个控制台应用程序，可以选择一个空的控制台应用程序。

创建程序之后把第一步中得到的三个文件copy到工程中。

由于我的电脑是win 7 64bit（win8 64bit），matlab是64bit，所以应该选择x64,而不是win32平台。

a)修改平台参数，为x64

生成 ---> 配置管理器 

b）配置包含目录与库目录

项目 ----> 属性 ----> vc++目录

包含目录：

D:\Program Files\MATLAB\R2012a\extern\include

库目录：

D:\Program Files\MATLAB\R2012a\extern\lib\win64\microsoft

C1）配置附加依赖项

右键MatlabTest解决方案->属性->链接器->输入

在“附加依赖项中”中添加相应的静态链接库文件。对于需要添加的静态库文件的数量和名称，根据需要添加。

libmx.lib

libeng.lib

libmex.lib

libmat.lib

…………

根据需要后续补上。

c2)配置附加依赖项 ， 这里根据项目的不同，依赖的文件不同，这里测试依赖的是"mclmcrrt.lib"和"libspline.lib"这两个lib，第一是库lib，第二个是我们生成的lib.文件。所依赖的lib文件在库目录已经说明了，

路径为：D:\Program Files\MATLAB\R2012a\extern\lib\win64\microsoft下。

这里有两种解决方案，第一种在vs中配置。

第一种在vs中配置。建议采用第二种方法！！！！因为第一种不同链接库配置的lib会不一样

项目 ----> 属性 ----> 连接器 ----> 输入 

第二种方法是，在文件中直接引入lib文件。

做完以上工作后，我们新建一个主函数作为入口函数，具体测试代码如下:

#include "libspline.h"    //增加头文件
#include <cmath>
#include <iostream>
#include <iomanip>
using namespace std;

#pragma comment(lib,"mclmcrrt.lib")
#pragma comment(lib,"libspline.lib")

int main()
{
    //初始化lib（必须）
    if (!libsplineInitialize())
        return -1;

    int i, j;
    double x[1][11], y[1][11];
    for(i=0; i<11; i++)
    {
        x[0][i] = i;
        y[0][i] = sin(x[0][i]);
    }

    double xx[1][41];
    for(i=0; i<41; i++)
        xx[0][i] = i*0.25;

    double yy[1][41];

    mwArray mwX(1,11,mxDOUBLE_CLASS);
    mwArray mwY(1,11,mxDOUBLE_CLASS);
    mwArray mwXX(1,41,mxDOUBLE_CLASS);
    mwArray mwYY(1,41,mxDOUBLE_CLASS);
    mwX.SetData(*x, 11);
    mwY.SetData(*y, 11);
    mwXX.SetData(*xx, 41);
    mwYY.SetData(*yy, 41);

    spline(1, mwYY, mwX, mwY, mwXX);    //调用spline

    cout<<"yy = "<<endl;
    i = 0;
    for(j = 0; j < 41; j++)
    {
        //Get第一个参数表示用1个下标访问元素，j+1是列号（MATLAB下标从1开始，而C++从0开始，故做+1操作）
        yy[0][j] = mwYY.Get(1,j+1);
        cout<<setprecision(4)<<right<<setw(10)<<yy[0][j];
        i++;
        if(i%7 == 0) cout<<endl;    //换行
    }
    cout<<endl;

    //终止调用
    libsplineTerminate();

    return 0;
}

运行结果如图：

比较这个结果与最开始我们测试matlab运行的结果，测试通过。matlab配置完成。

ps说明：配置过程中遇到的问题：

配置时经常遇到 LINK2019的错误。这种错误就是典型的lib缺失导入的问题。

main.obj : error LNK2019: 无法解析的外部符号 mclGetMatrix_proxy，该符号在函数 "public: __cdecl mwArray::mwArray(unsigned __int64,unsigned __int64,enum mxClassID,enum mxComplexity)" ([email protected]@[email protected][email protected]@[email protected]@@Z) 中被引用
1>main.obj : error LNK2019: 无法解析的外部符号 mclcppGetLastError_proxy，该符号在函数 "public: static void __cdecl mwException::raise_error(void)" ([email protected]@@SAXXZ) 中被引用
1>main.obj : error LNK2019: 无法解析的外部符号 mclcppCreateError_proxy，该符号在函数 "public: __cdecl mwException::mwException(void)" ([email protected]@[email protected]) 中被引用
1>main.obj : error LNK2019: 无法解析的外部符号 ref_count_obj_addref_proxy，该符号在函数 "public: __cdecl mwException::mwException(class mwException const &)" ([email protected]@[email protected]@@Z) 中被引用
1>main.obj : error LNK2019: 无法解析的外部符号 ref_count_obj_release_proxy，该符号在函数 "public: virtual __cdecl mwException::~mwException(void)" ([email protected]@[email protected]) 中被引用
1>main.obj : error LNK2019: 无法解析的外部符号 error_info_get_message_proxy，该符号在函数 "public: virtual char const * __cdecl mwException::what(void)const " ([email protected]@@UEBAPEBDXZ) 中被引用
1>main.obj : error LNK2019: 无法解析的外部符号 array_ref_getV_int_proxy，该符号在函数 "public: class mwArray __cdecl mwArray::GetPromoted(unsigned __int64,...)" ([email protected]@@[email protected]_KZZ) 中被引用
1>main.obj : error LNK2019: 无法解析的外部符号 array_ref_set_numeric_mxDouble_proxy，该符号在函数 "public: void __cdecl mwArray::SetData(double *,unsigned __int64)" ([email protected]@@[email protected]) 中被引用
1>main.obj : error LNK2019: 无法解析的外部符号 array_ref_get_numeric_mxDouble_proxy，该符号在函数 "public: __cdecl mwArray::operator double(void)const " ([email protected]@QEBANXZ) 中被引用

这里是因为缺少：mclmcrrt.lib

#pragma comment(lib,"mclmcrrt.lib")

即可解决。