我在 C 中有一個稀疏矩陣實作，我使用 pybind11 將它公開給 python。這是問題所在：
>>> D1 = phc.SparseMatrix(3, [[0],[1],[2]])
>>> D1.cData
[[0], [1], [2]]
>>> D1.cData[1] = [1,2]
>>> D1.cData
[[0], [1], [2]] #Should be [[0], [1,2], [2]]
在 python 中，我無法SparseMatrix.cData使用賦值運算子更改屬性的內容。我可以用更改整個串列D1.cData = [[1],[2],[3]]。這種行為讓我感到困惑。D1.cData只是一個串列，所以我希望上面的代碼可以作業。
我懷疑它與我的 pybind11 代碼有關，因為這種行為在 python 定義的自定義類中不存在。但我不知道出了什么問題（我是新手程式員）。以下是源代碼資訊：
Python 系結
#include <pybind11/pybind11.h>
#include <pybind11/stl.h>
namespace py = pybind11;
#include <SparseMatrix.h>
namespace phc = ph_computation;
using SparseMatrix = phc::SparseMatrix;
using Column = phc::Column;
using CData = phc::CData;
PYBIND11_MODULE(ph_computations, m)
{
m.doc() = "ph_computations python bindings";
using namespace pybind11::literals;
m.def("add_cols", &phc::add_cols);//begin SparseMatrix.h
py::class_<SparseMatrix>(m, "SparseMatrix")
.def(py::init<size_t, CData>())
.def(py::init<std::string>())
.def_readwrite("n_rows", &SparseMatrix::n_rows)
.def_readwrite("n_cols", &SparseMatrix::n_cols)
.def_readwrite("cData", &SparseMatrix::cData)
.def("__neq__", &SparseMatrix::operator!=)
.def("__eq__", &SparseMatrix::operator==)
.def("__add__", &SparseMatrix::operator )
.def("__mul__", &SparseMatrix::operator*)
.def("transpose", &SparseMatrix::transpose)
.def("__str__", &SparseMatrix::print)
.def("save", &SparseMatrix::save)
;
m.def("identity", &phc::make_identity);
m.def("matching_pivots", &phc::matching_pivots);//end SparseMatrix.h
}
稀疏矩陣.h
#pragma once
#include <iostream>
#include <sstream>
#include <fstream>
#include <string>
#include <iterator>
#include <algorithm>
#include <vector>
#include <stdexcept>
namespace ph_computation{
using Int = int;
using Column = std::vector<Int>;//a Column is represented by a vector of indices
using CData = std::vector<Column>;//a matrix is represented by a vector of Columns
//Add columns in Z2
Column add_cols(const Column& c1, const Column& c2);
struct SparseMatrix
{
size_t n_rows{0};
size_t n_cols{0};
CData cData;
SparseMatrix()=default;
SparseMatrix(size_t n_rows_, CData cData_):
n_rows(n_rows_), n_cols(cData_.size()), cData(cData_){}
SparseMatrix(std::string path);
bool operator!=(const SparseMatrix &other) const;
bool operator==(const SparseMatrix &other) const;
SparseMatrix operator (const SparseMatrix &other) const;
SparseMatrix operator*(const SparseMatrix &other) const;
void transpose();
void print() const;
void save(std::string path);
};
SparseMatrix make_identity(size_t n_cols_);
bool matching_pivots(const SparseMatrix& a, const SparseMatrix& b);
}
SparseMatrix.cpp（你可能不需要這個）
#include <SparseMatrix.h>
namespace ph_computation {
Column add_cols(const Column& c1, const Column& c2){
Column c3;
int idx1{0};
int idx2{0};
while(idx1 < c1.size() && idx2 < c2.size()){
if(c1[idx1] < c2[idx2]){
c3.push_back(c1[idx1]);
idx1;
}
else if(c1[idx1] > c2[idx2]){
c3.push_back(c2[idx2]);
idx2;
}
else {
idx1;
idx2;
}
}
if (idx1 < c1.size()){
c3.insert(c3.end(), std::next(c1.begin(), idx1), c1.end());
}
else if (idx2 < c2.size()){
c3.insert(c3.end(), std::next(c2.begin(), idx2), c2.end());
}
return c3;
}
SparseMatrix make_identity(size_t n_cols_){
CData cData_(n_cols_);
for (int j = 0; j < n_cols_; j){
cData_[j] = {j};
}
return SparseMatrix(n_cols_, cData_);
}
SparseMatrix::SparseMatrix(std::string path){
std::fstream f_in;
f_in.open(path, std::ios::in);
if(f_in.is_open()){
std::string n_rows_line;
std::getline(f_in, n_rows_line); //first line of file contains number of rows
n_rows = std::stoi(n_rows_line);
std::string n_cols_line;
std::getline(f_in, n_cols_line); //second line of file contains number of cols
n_cols = std::stoi(n_cols_line);
CData cData_(n_cols);
cData = cData_;
std::string line;
int j = 0;
int nnz, data;
while (std::getline(f_in, line)){
std::stringstream line_str = std::stringstream(line);
while (line_str >> nnz){
Column col_j(nnz);
for (int i =0; i < nnz; i){
line_str >> data;
col_j[i] = data;
}
cData[j] = col_j;
}
j;
}
f_in.close();
}
else{
throw std::runtime_error("File did not open.");
}
}
bool SparseMatrix::operator!=(const SparseMatrix &other) const{
if (n_rows != other.n_rows || cData != other.cData){
return true;
}
return false;
}
bool SparseMatrix::operator==(const SparseMatrix &other) const{
return !(*this != other);
}
SparseMatrix SparseMatrix::operator (const SparseMatrix &other) const{
if (n_rows != other.n_rows || n_cols != other.n_cols){
throw std::invalid_argument("Matrices must have same dimension to add.");
}
CData ans_cData;
for (int j = 0; j < n_cols; j){
ans_cData.push_back(add_cols(cData[j], other.cData[j]));
}
return SparseMatrix(n_rows, ans_cData);
}
SparseMatrix SparseMatrix::operator*(const SparseMatrix &other) const{
if(n_cols != other.n_rows){
throw std::invalid_argument("Matrices must have compatible dimensions.");
}
size_t ans_rows = n_rows;
CData ans_cData(other.n_cols);
SparseMatrix ans(ans_rows, ans_cData);
for(int j =0; j<ans.n_cols; j){
for(int idx : other.cData[j]){
ans.cData[j] = add_cols(ans.cData[j], cData[idx]);
}
}
return ans;
}
void SparseMatrix::transpose(){
CData cData_T(n_rows);
for(int j =0; j<n_cols; j){
if(!cData[j].empty()){
for(int x: cData[j]){
cData_T[x].push_back(j);
}
}
}
cData = cData_T;
n_rows = n_cols;
n_cols = cData.size();
}
void SparseMatrix::print() const{
for (int i = 0; i < n_rows; i){
for (int j = 0; j < n_cols; j){
if (cData[j].empty())
{std::cout << " 0";}
else if (std::binary_search(cData[j].begin(), cData[j].end(), i))//Assumes row indices
{std::cout << " 1";} //are ordered
else
{std::cout << " 0";}
if (n_cols-1 == j)
{std::cout << " \n";}
}
}
}
void SparseMatrix::save(std::string path){
std::fstream f_out;
f_out.open(path, std::ios::out);
if(f_out.is_open()){
f_out << n_rows << "\n";
f_out << n_cols << "\n";
for(int j = 0; j < n_cols; j){
int col_j_sz = cData[j].size();
f_out << col_j_sz;
for(int i = 0; i < col_j_sz; i){
f_out << " " << cData[j][i];
}
f_out << "\n";
}
f_out.close();
}
else{
throw std::runtime_error("File did not open.");
}
}
bool matching_pivots(const SparseMatrix& a, const SparseMatrix& b){
if(a.n_rows != b.n_rows || a.n_cols != b.n_cols){
throw std::invalid_argument("Input matrices must have the same size.");
}
for (int j = 0; j<a.n_cols; j){
bool a_j_empty = a.cData[j].empty();
bool b_j_empty = b.cData[j].empty();
if (a_j_empty != b_j_empty){
return false;
}
else if (!a_j_empty){
if(a.cData[j].back() != b.cData[j].back()){
return false;
}
}
}
return true;
}
} // namespace ph_computation
uj5u.com熱心網友回復：
我在這里的 pybind11 檔案中找到了答案：https ://pybind11.readthedocs.io/en/stable/advanced/cast/stl.html?highlight=opaque#making-opaque-types
顯然，STL容器資料成員可以在python中被完全覆寫，但是通過串列方法修改資料成員是行不通的。我不太明白，但上面的鏈接回答了這個問題。
轉載請註明出處，本文鏈接：https://www.uj5u.com/gongcheng/520997.html