犰狳的静态链接

时间:2018-01-28 14:47:42

标签: c++ static-libraries armadillo

我试图将armadillo库静态链接到Visual Studio 2017 for C ++应用以下步骤,但无济于事。平台设置为x64

  1. C / C ++ - >一般 - >其他包含目录 - > $(SolutionDir)依赖\包括
  2. 在源文件中写了#include "armadillo"(尝试了#include< armadillo>)。
  3. 链接器 - >输入 - >附加依赖性 - > blas_win64_MT.lib; lapack_win64_MT.lib
  4. 链接器 - >一般 - >其他图书馆目录 - > $(SolutionDir)依赖关系\ lib_win64
  5. 注意:

      

    include 是包含 armadillo armadillo_bits 的文件夹的名称第1步中的em> 文件夹。

         

    lib_win64 blas_win64_MT.lib lapack_win64_MT的文件夹的名称第4步中的.lib

    当我尝试编译时,遇到以下错误:

      

    C:\ ........ \依赖性\包括\ armadillo_bits \ arma_rng.hpp(444):   错误C2760:语法错误:意外标记'标识符',预期';'

         

    C:\ ........ \依赖性\包括\ armadillo_bits \ arma_rng.hpp(524):   注意:请参阅类模板实例化的引用   正在编译“arma::arma_rng::randn<std::complex<_Other>>

    arma_rng.hpp的代码,直接来自armadillo库代码。

    template<typename T>
    struct arma_rng::randn < std::complex<T> > 
      {
      inline
      operator std::complex<T> () const
        {
        T a, b; //************line 444***************
    
        arma_rng::randn<T>::dual_val(a, b);
    
        return std::complex<T>(a, b);
        }
    
    
      inline
      static
      void
      fill(std::complex<T>* mem, const uword N)
        {
        ...
    
      }; //************line 524***************
    

    这是一个直接来自armadillo示例的代码来测试我是否已经正确链接了犰狳,目前还没有实现头文件:

    #include <iostream>
    #include <armadillo>
    
    using namespace std;
    using namespace arma;
    
    // Armadillo documentation is available at:
    // http://arma.sourceforge.net/docs.html
    
    int
    main(int argc, char** argv)
      {
      cout << "Armadillo version: " << arma_version::as_string() << endl;
    
      mat A(2,3);  // directly specify the matrix size (elements are uninitialised)
    
      cout << "A.n_rows: " << A.n_rows << endl;  // .n_rows and .n_cols are read only
      cout << "A.n_cols: " << A.n_cols << endl;
    
      A(1,2) = 456.0;  // directly access an element (indexing starts at 0)
      A.print("A:");
    
      A = 5.0;         // scalars are treated as a 1x1 matrix
      A.print("A:");
    
      A.set_size(4,5); // change the size (data is not preserved)
    
      A.fill(5.0);     // set all elements to a particular value
      A.print("A:");
    
      // endr indicates "end of row"
      A << 0.165300 << 0.454037 << 0.995795 << 0.124098 << 0.047084 << endr
        << 0.688782 << 0.036549 << 0.552848 << 0.937664 << 0.866401 << endr
        << 0.348740 << 0.479388 << 0.506228 << 0.145673 << 0.491547 << endr
        << 0.148678 << 0.682258 << 0.571154 << 0.874724 << 0.444632 << endr
        << 0.245726 << 0.595218 << 0.409327 << 0.367827 << 0.385736 << endr;
    
      A.print("A:");
    
      // determinant
      cout << "det(A): " << det(A) << endl;
    
      // inverse
      cout << "inv(A): " << endl << inv(A) << endl;
    
      // save matrix as a text file
      A.save("A.txt", raw_ascii);
    
      // load from file
      mat B;
      B.load("A.txt");
    
      // submatrices
      cout << "B( span(0,2), span(3,4) ):" << endl << B( span(0,2), span(3,4) ) << endl;
    
      cout << "B( 0,3, size(3,2) ):" << endl << B( 0,3, size(3,2) ) << endl;
    
      cout << "B.row(0): " << endl << B.row(0) << endl;
    
      cout << "B.col(1): " << endl << B.col(1) << endl;
    
      // transpose
      cout << "B.t(): " << endl << B.t() << endl;
    
      // maximum from each column (traverse along rows)
      cout << "max(B): " << endl << max(B) << endl;
    
      // maximum from each row (traverse along columns)
      cout << "max(B,1): " << endl << max(B,1) << endl;
    
      // maximum value in B
      cout << "max(max(B)) = " << max(max(B)) << endl;
    
      // sum of each column (traverse along rows)
      cout << "sum(B): " << endl << sum(B) << endl;
    
      // sum of each row (traverse along columns)
      cout << "sum(B,1) =" << endl << sum(B,1) << endl;
    
      // sum of all elements
      cout << "accu(B): " << accu(B) << endl;
    
      // trace = sum along diagonal
      cout << "trace(B): " << trace(B) << endl;
    
      // generate the identity matrix
      mat C = eye<mat>(4,4);
    
      // random matrix with values uniformly distributed in the [0,1] interval
      mat D = randu<mat>(4,4);
      D.print("D:");
    
      // row vectors are treated like a matrix with one row
      rowvec r;
      r << 0.59119 << 0.77321 << 0.60275 << 0.35887 << 0.51683;
      r.print("r:");
    
      // column vectors are treated like a matrix with one column
      vec q;
      q << 0.14333 << 0.59478 << 0.14481 << 0.58558 << 0.60809;
      q.print("q:");
    
      // convert matrix to vector; data in matrices is stored column-by-column
      vec v = vectorise(A);
      v.print("v:");
    
      // dot or inner product
      cout << "as_scalar(r*q): " << as_scalar(r*q) << endl;
    
      // outer product
      cout << "q*r: " << endl << q*r << endl;
    
      // multiply-and-accumulate operation (no temporary matrices are created)
      cout << "accu(A % B) = " << accu(A % B) << endl;
    
      // example of a compound operation
      B += 2.0 * A.t();
      B.print("B:");
    
      // imat specifies an integer matrix
      imat AA;
      imat BB;
    
      AA << 1 << 2 << 3 << endr << 4 << 5 << 6 << endr << 7 << 8 << 9;
      BB << 3 << 2 << 1 << endr << 6 << 5 << 4 << endr << 9 << 8 << 7;
    
      // comparison of matrices (element-wise); output of a relational operator is a umat
      umat ZZ = (AA >= BB);
      ZZ.print("ZZ:");
    
      // cubes ("3D matrices")
      cube Q( B.n_rows, B.n_cols, 2 );
    
      Q.slice(0) = B;
      Q.slice(1) = 2.0 * B;
    
      Q.print("Q:");
    
      // 2D field of matrices; 3D fields are also supported
      field<mat> F(4,3); 
    
      for(uword col=0; col < F.n_cols; ++col)
      for(uword row=0; row < F.n_rows; ++row)
        {
        F(row,col) = randu<mat>(2,3);  // each element in field<mat> is a matrix
        }
    
      F.print("F:");
    
      return 0;
      }
    

3 个答案:

答案 0 :(得分:1)

请将您的VS2017平台工具集更改为v140而不是v141。然后编译,它必须工作。

答案 1 :(得分:1)

对于面临同样问题的其他人,使用VC++ 2015.3 v140 toolset为我工作,将OpenBLASarmadillo编译为静态库。

这些是Visual Studio 2017( VS2017 )所需的步骤:

  • 根据需要安装v140工具集:
    • 修改 VS2017 安装(即详情here
    • 查看桌面开发C++
    • 在右侧,摘要下单击使用C ++进行桌面开发
    • 列表底部的
    • 检查用于桌面的VC ++ 2015.3 v140工具集(x86,x64)
  • 接下来,您需要告诉编译器使用v140而不是v141,因此:
    • 右键单击 VS2017
    • 中的项目名称
    • 转到配置属性常规平台工具集
    • 选择 Visual Studio 2015(v140)

现在您应该能够#include <armadillo>并编译您的代码。

备注:

  • 您仍然需要确保设置正确的包含路径(即,如果您通过 Nuget Package Manager 安装armadillo,只需按照上述步骤操作即可

希望这有帮助。

答案 2 :(得分:0)

这似乎是由Visual Studio 2017引起的 BUG ,它与 一致性模式 有关,最近已在默认情况下启用Visual Studio。他们尝试将其修复(详细信息here)。

VS2017 (V141,而不是安装V140)中工作的变通办法是 禁用符合性模式 。您可以尝试这样方式:

  • 项目属性-> C / C ++->语言->一致性模式-> 禁用