312 lines
8.9 KiB
C++
312 lines
8.9 KiB
C++
#include <mex.h>
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#include <mat.h>
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#include <iostream>
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#include <algorithm>
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#include <string>
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#include <unordered_set>
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#include <ctime>
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#include <vector>
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#include <queue>
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#include <memory>
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#include <thread>
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#include <mutex>
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#include <condition_variable>
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#include <future>
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#include <functional>
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#include <stdexcept>
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#include <unordered_map>
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#include <set>
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#include <fstream>
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#include <random>
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#include <cmath>
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#include <stdlib.h>
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#include <limits.h>
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#include <atomic>
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using std::cout;
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using std::endl;
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using namespace std;
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#define STRING_BUF_SIZE 204800
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// 将matlab存储方式转换成c存储方式
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#define TRANS_ROW_COL(dst, src, rowNum, colNum) \
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for (int rowI = 0; rowI < rowNum; ++rowI) { \
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for (int colJ = 0; colJ < colNum; ++colJ) { \
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dst[rowI * colNum + colJ] = src[colJ * rowNum + rowI]; \
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} \
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}
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class ThreadPool {
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public:
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ThreadPool(size_t);
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template<class F, class... Args>
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auto enqueue(F&& f, Args&&... args)
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->std::future<typename std::result_of<F(Args...)>::type>;
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~ThreadPool();
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private:
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// need to keep track of threads so we can join them
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std::vector< std::thread > workers;
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// the task queue
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std::queue< std::function<void()> > tasks;
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// synchronization
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std::mutex queue_mutex;
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std::condition_variable condition;
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bool stop;
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};
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// the constructor just launches some amount of workers
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inline ThreadPool::ThreadPool(size_t threads)
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: stop(false)
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{
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for (size_t i = 0;i < threads;++i)
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workers.emplace_back(
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[this]
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{
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for (;;)
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{
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std::function<void()> task;
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{
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std::unique_lock<std::mutex> lock(this->queue_mutex);
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this->condition.wait(lock,
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[this] { return this->stop || !this->tasks.empty(); });
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if (this->stop && this->tasks.empty())
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return;
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task = std::move(this->tasks.front());
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this->tasks.pop();
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}
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task();
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}
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}
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);
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}
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// add new work item to the pool
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template<class F, class... Args>
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auto ThreadPool::enqueue(F && f, Args&&... args)
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-> std::future<typename std::result_of<F(Args...)>::type>
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{
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using return_type = typename std::result_of<F(Args...)>::type;
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auto task = std::make_shared< std::packaged_task<return_type()> >(
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std::bind(std::forward<F>(f), std::forward<Args>(args)...)
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);
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std::future<return_type> res = task->get_future();
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{
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std::unique_lock<std::mutex> lock(queue_mutex);
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// don't allow enqueueing after stopping the pool
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if (stop)
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throw std::runtime_error("enqueue on stopped ThreadPool");
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tasks.emplace([task]() { (*task)(); });
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}
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condition.notify_one();
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return res;
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}
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// the destructor joins all threads
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inline ThreadPool::~ThreadPool()
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{
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{
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std::unique_lock<std::mutex> lock(queue_mutex);
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stop = true;
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}
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condition.notify_all();
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for (std::thread& worker : workers)
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worker.join();
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}
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// 读取一维cell字符串并转换成大写
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inline bool ReadWord1DCell(const mxArray* pMxArray, vector<string>& vStr) {
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mxArray* pCell = nullptr;
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int rowNum, colNum;
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char* strBuf = new char[STRING_BUF_SIZE];
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rowNum = (int)mxGetM(pMxArray);
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colNum = (int)mxGetN(pMxArray);
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vStr.resize(rowNum * colNum);
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for (int i = 0; i < rowNum; ++i) {
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for (int j = 0; j < colNum; ++j) {
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pCell = mxGetCell(pMxArray, j * rowNum + i);
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if (mxGetString(pCell, strBuf, STRING_BUF_SIZE) != 0) {
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cout << "String is too large to fit in the buffer! " << i + 1 << '\t' << j + 1 << endl;
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return false;
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}
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vStr[i * colNum + j] = strBuf;
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auto& lastStr = vStr[i * colNum + j];
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transform(lastStr.cbegin(), lastStr.cend(), lastStr.begin(), ::toupper); // 转成大写
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}
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}
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delete[]strBuf;
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return true;
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}
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// 读取二维cell字符串并转换成大写
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inline bool ReadWord2DCell(const mxArray* pMxArray, vector<vector<string>>& vvStr) {
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mxArray* pCell = nullptr;
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int rowNum, colNum;
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rowNum = (int)mxGetM(pMxArray);
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colNum = (int)mxGetN(pMxArray);
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for (int i = 0; i < rowNum; ++i) {
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for (int j = 0; j < colNum; ++j) {
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pCell = mxGetCell(pMxArray, j * rowNum + i);
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vvStr.push_back(vector<string>());
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ReadWord1DCell(pCell, vvStr.back());
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}
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}
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return true;
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}
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// 读取由一维cell包裹的double数据，每个cell是一个一维的double数组
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inline void ReadDoulbe1DCell(const mxArray* pMxArray, vector<vector<double> >& vvData) {
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// 读取fr数值
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int rowNum = (int)mxGetM(pMxArray);
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int colNum = (int)mxGetN(pMxArray);
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for (int i = 0; i < rowNum; ++i) {
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for (int j = 0; j < colNum; ++j) {
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mxArray* pCell = mxGetCell(pMxArray, j * rowNum + i);
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int childRowNum = (int)mxGetM(pCell);
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int childColNum = (int)mxGetN(pCell);
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vvData.push_back(vector<double>());
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vvData.back().resize(childRowNum * childColNum);
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double* pVal = (double*)mxGetData(pCell); //获取数据指针
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TRANS_ROW_COL(vvData.back(), pVal, childRowNum, childColNum); // 行列存储方式转换
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}
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}
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}
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// 将结果写入mxArray, 作为后续的返回值
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mxArray* writeToMatDouble(const double* data, int rowNum, int colNum) {
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mxArray* pWriteArray = NULL;//matlab格式矩阵
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int len = rowNum * colNum;
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//创建一个rowNum*colNum的矩阵
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pWriteArray = mxCreateDoubleMatrix(rowNum, colNum, mxREAL);
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//把data的值赋给pWriteArray指针
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memcpy((void*)(mxGetPr(pWriteArray)), (void*)data, sizeof(double) * len);
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return pWriteArray; // 赋值给返回值
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}
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/* 多线程计算信息熵 */
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struct TPEntropyMean {
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vector<string>* pvDs;
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vector<double>* pvFr;
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vector<unordered_set<string>>* pvusAbsWord;
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vector<double>* pvHs;
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vector<double>* pvHd;
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};
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void ThreadCalcEntropyMean(TPEntropyMean& param) {
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vector<string>& vDs = *param.pvDs; // 这一组ds
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vector<double>& vFr = *param.pvFr; // frequency
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vector<unordered_set<string>>& vusAbsWord = *param.pvusAbsWord;
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vector<double>& vHs = *param.pvHs;
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vector<double>& vHd = *param.pvHd;
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const int numAbs = vusAbsWord.size();
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const int numDsWord = vDs.size(); // 这一组数据中包含的单词数量
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// 检查知识颗粒中的词语是否出现在pubmed摘要的词语中
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for (int i = 0; i < numAbs; ++i) {
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for (int j = 0; j < numDsWord; ++j) {
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if (vusAbsWord[i].find(vDs[j]) != vusAbsWord[i].end()) { // 这一组单词中的j索引位置的单词在第i个文献中出现过
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vHs[i] -= vFr[j] * log2(vFr[j]);
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}
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}
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vHd[i] = vHs[i] / vusAbsWord[i].size();
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}
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}
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/*
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输入：
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1. ds: 知识颗粒中的信息，应该也是摘要，分割成了字符串，大写的。
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2. frr: ds中每个单词对应的频率。
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3. ws: 文献的摘要，被切割成特定的长度了，字符串已经分割好了。
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[4]. numThread
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输出：
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1. hs: 信息熵，二维[len(ds)][len(ws)]
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2. hd: 每个单词的平均信息熵，维度同hs
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*/
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void mexFunction(int nlhs, mxArray* plhs[], int nrhs, const mxArray* prhs[]) {
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if (nrhs < 3) {
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cout << "At least 3 arguments should be given for this function!" << endl;
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return;
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}
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clock_t begin = clock(), mid, finish;
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vector<vector<string> > vvDs; // 每个知识颗粒的ds矩阵（词汇矩阵）
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vector<vector<double> > vvFr; // 词汇对应的频率
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ReadWord2DCell(prhs[0], vvDs);
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ReadDoulbe1DCell(prhs[1], vvFr);
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vector<vector<string>> vvWs;
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ReadWord2DCell(prhs[2], vvWs); // 文献摘要的字符串数组
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int numThread = 1;
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if (nrhs > 3) {
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double* pNumThread = (double*)mxGetData(prhs[3]);
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numThread = (int)pNumThread[0];
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if (numThread < 1) numThread = 1;
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}
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vector<unordered_set<string>> vusAbsWord(vvWs.size()); // 将每篇文章摘要的单词放入hash表
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// 将处理摘要之后的每个词语放入hash表
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for (int i=0; i<vvWs.size(); ++i) {
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for (auto& word : vvWs[i]) {
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vusAbsWord[i].insert(word);
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}
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}
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finish = clock();
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cout << "Load Data time: " << (double)(finish - begin) / CLOCKS_PER_SEC << " s" << endl << flush;
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int numGroup = vvDs.size();
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int numAbs = vvWs.size(); // 摘要个数
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// 计算结果
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vector<vector<double>> vvHs(numGroup, vector<double>(numAbs));
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vector<vector<double>> vvHd(numGroup, vector<double>(numAbs));
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vector<string>* pvDs;
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vector<double>* pvFr;
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vector<unordered_set<string>>* pvusAbsWord;
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vector<double>* pvHs;
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vector<double>* pvHd;
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/* 多线程计算信息熵 */
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ThreadPool thPool(numThread);
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for (int groupIdx = 0; groupIdx < numGroup; ++groupIdx) { // 遍历知识颗粒中的每一组
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TPEntropyMean tp = { &vvDs[groupIdx], &vvFr[groupIdx], &vusAbsWord, &vvHs[groupIdx], &vvHd[groupIdx] };
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thPool.enqueue(ThreadCalcEntropyMean, tp);
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}
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thPool.~ThreadPool();
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// ofstream ofs("d:\\result_hs.txt");
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// for (int i = 0; i < numGroup; ++i) {
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// for (int j = 0; j < numAbs; ++j) {
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// ofs << vvHs[i][j] << ' ';
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// }
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// ofs << endl;
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// }
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// ofs.close();
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/* 将结果写入返回值 */
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if (nlhs > 0) {
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vector<double> vData(numGroup * numAbs);
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for (int i = 0; i < numGroup; ++i) for (int j = 0; j < numAbs; ++j) vData[j * numGroup + i] = vvHs[i][j];
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plhs[0] = writeToMatDouble(vData.data(), numGroup, numAbs);
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}
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if (nlhs > 1) {
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vector<double> vData(numGroup * numAbs);
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for (int i = 0; i < numGroup; ++i) for (int j = 0; j < numAbs; ++j) vData[j * numGroup + i] = vvHd[i][j];
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plhs[1] = writeToMatDouble(vData.data(), numGroup, numAbs);
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}
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finish = clock();
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cout << "Calc Entropy and Mean Total time: " << (double)(finish - begin) / CLOCKS_PER_SEC << " s" << endl;
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}
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/* 供main调试调用 */
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void mexFunctionWrap(int nlhs, mxArray* plhs[], int nrhs, const mxArray* prhs[]) {
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mexFunction(nlhs, plhs, nrhs, prhs);
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} |