c++ - Eigen Sparse value_Ptr 显示零，同时忽略有效值

Question

我不明白当我尝试迭代稀疏矩阵的 valuePtr 时得到的结果。这是我的代码。

#include <iostream>
#include <vector>
#include <Eigen/Sparse>

using namespace Eigen;

int main()
{
  SparseMatrix<double> sm(4,5);

  std::vector<int> cols = {0,1,4,0,4,0,4};
  std::vector<int> rows = {0,0,0,2,2,3,3};
  std::vector<double> values = {0.2,0.4,0.6,0.3,0.7,0.9,0.2};

  for(int i=0; i < cols.size(); i++)
      sm.insert(rows[i], cols[i]) = values[i];

  std::cout << sm << std::endl;

  int nz = sm.nonZeros();
  std::cout << "non_zeros : " << nz << std::endl;

  for (auto it = sm.valuePtr(); it != sm.valuePtr() + nz; ++it)
    std::cout << *it << std::endl;

  return 0;
}

Output:

0.2 0.4 0 0 0.6  // The values are in the matrix
0 0 0 0 0 
0.3 0 0 0 0.7 
0.9 0 0 0 0.2 

non_zeros : 7  
0.2            // but valuePtr() does not point to them
0.3            // I expected: 0.2, 0.3, 0.9, 0.4, 0.6, 0.7, 0.2
0.9
0
0.4
0
0

我不明白为什么我会得到零，这是怎么回事？

Answer 1

根据documentation对于稀疏矩阵:

Unlike the compressed format, there might be extra space inbetween the nonzeros of two successive columns (resp. rows) such that insertion of new non-zero can be done with limited memory reallocation and copies.

[...]

A call to the function makeCompressed() turns the matrix into the standard compressed format compatible with many library.

For example :

This storage scheme is better explained on an example. The following matrix

0  3  0   0   0
22 0  0   0   17
7  5  0   1   0
0  0  0   0   0
0  0  14  0   8

and one of its possible sparse, column major representation:

Values:       22  7   _   3   5   14  _   _   1   _   17  8
InnerIndices: 1   2   _   0   2   4   _   _   2   _   1   4

[...]

The "_" indicates available free space to quickly insert new elements.

由于 valuePtr() 只是返回一个指向 Values 数组的指针，因此除非您压缩矩阵，否则您将看到空格(打印的零) .