141 lines
5.7 KiB
C++
141 lines
5.7 KiB
C++
#include "FindPeaksBySvd.h"
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using namespace arma;
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std::vector<FindPeaksBySvd::PeakInfo> FindPeaksBySvd::FindPeaks(const arma::mat &spec_data, int step_w) throw(std::string)
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{
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std::vector<FindPeaksBySvd::PeakInfo> peak_info_vec;
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try {
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const arma::vec& spec_data_col0 = spec_data.col(0);
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const arma::vec& spec_data_col1 = spec_data.col(1);
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int m = spec_data_col1.n_elem; // 能谱长度
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int n = (step_w == -1) ? 7 : step_w; // 窗口大小（默认7）
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int ns = ceil((n - 1) / 2.0); // 窗口半宽
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// 初始化变量
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vec kosin(m, fill::zeros);
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vec Smax(m, fill::zeros);
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vec Smin(m, fill::zeros);
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int k = 0; // 索引计数器（对应Matlab的k）
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// 滑动窗口遍历+SVD分析
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for (int i = 0; i < m; i++) { // Armadillo默认0索引，Matlab是1索引，需对应转换
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k++;
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vec vec2; // 局部窗口数据
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// 边界处理：左边界
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if (k <= ns) {
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vec2 = spec_data_col1.subvec(0, n - 1);
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}
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// 右边界
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else if (k >= m - ns) { // Matlab: k>=m-ns-1，因索引差异调整
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vec2 = spec_data_col1.subvec(m - n, m - 1);
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}
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// 中间区域：以i为中心的n点窗口
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else {
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int start = i - floor((n - 1) / 2.0);
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int end = i + ceil((n - 1) / 2.0);
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vec2 = spec_data_col1.subvec(start, end);
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}
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// 构造矩阵M（2列：基线参考+局部数据）
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vec vec1(n, fill::ones);
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double min_val = vec2.min();
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mat M(n, 2);
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M.col(0) = min_val * vec1;
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M.col(1) = vec2;
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// SVD分解（Armadillo svd返回U,S,V^T，与Matlab一致）
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mat U, V;
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vec S;
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svd(U, S, V, M); // S为奇异值向量（降序排列）
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// 存储最大/最小奇异值
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Smax(i) = S(0);
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Smin(i) = S(1);
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// 计算余弦相似度（kosin）
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double mean_vec2 = mean(vec2);
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vec mean_vec1 = mean_vec2 * vec1;
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double dot_prod = dot(vec2, mean_vec1);
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double norm_vec2 = norm(vec2);
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double norm_mean1 = norm(mean_vec1);
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kosin(i) = dot_prod / (norm_vec2 * norm_mean1 + 1e-8); // 加小值避免除零
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}
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// 计算峰识别指标DistV
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vec sin_kosin = sqrt(1 - pow(kosin, 2));
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vec DistV1 = sin_kosin % Smax;
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vec DistV2 = sin_kosin % Smin;
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double mean_DistV2 = mean(DistV2);
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vec DistV = DistV2 - 3 * sqrt(mean_DistV2);
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// 峰边界识别与参数提取
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int Lc = 0, Rc = 1;
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int nos = DistV.n_elem;
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for (int ch = 0; ch < nos - 1; ch++) { // 遍历
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if (DistV(ch) < 0 && DistV(ch + 1) >= 0) {
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// 左边界：DistV从负→正
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Lc = ch;
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} else if (DistV(ch) >= 0 && DistV(ch + 1) <= 0) {
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// 右边界：DistV从正→负
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Rc = ch;
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} else {
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continue;
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}
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// 计算峰参数
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if (Rc > Lc) {
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int wop = abs(Rc - Lc);
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if (wop <= 0)
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continue; // 无效宽度跳过
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// 提取峰区域数据
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vec peak_region = spec_data_col1.subvec(Lc, Rc);
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double height = peak_region.max();
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uword HWP_idx = peak_region.index_max(); // 峰值位置
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// 计算半高宽(FWHM)
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double half_height = height / 2.0;
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int left_half = 0, right_half = peak_region.n_elem - 1;
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// 找到左侧半高位置
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for (int i = HWP_idx; i >= 0; i--) {
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if (peak_region(i) <= half_height) {
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left_half = i;
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break;
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}
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}
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// 找到右侧半高位置
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for (int i = HWP_idx; i < peak_region.n_elem; i++) {
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if (peak_region(i) <= half_height) {
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right_half = i;
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break;
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}
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}
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// 计算半高宽（转换为原始坐标）
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double fwhm = (right_half - left_half + 1);
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// 计算峰面积（使用梯形法则）
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double area = 0.0;
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for (int i = 0; i < peak_region.n_elem - 1; i++) {
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// 梯形面积 = (上底 + 下底) * 高 / 2
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area += (peak_region(i) + peak_region(i + 1)) / 2.0;
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}
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// 峰中心
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int pl = round((Lc + Rc) / 2.0);
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// 筛选有效峰：峰宽>2且中心DistV>0
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// 修改20251126: 去除峰宽>2及“wop > 2”的判断条件
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if (DistV(pl - 1) > 0) { // pl-1转换为0索引
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int left = Lc;
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int width = wop + 1;
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int pos = Lc + HWP_idx;
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PeakInfo peak_info;
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peak_info.left = spec_data_col0.at(left);
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peak_info.width = spec_data_col0.at(width);
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peak_info.height = height;
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peak_info.pos = spec_data_col0.at(pos);
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peak_info.fwhm = fwhm;
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peak_info.area = area;
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peak_info_vec.push_back(peak_info);
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}
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}
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}
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}
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catch(const std::exception& e) {
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throw std::string("Find Peaks Exception, ") + std::string(e.what());
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}
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catch (...) {
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throw std::string("Find peaks unkonow exception");
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}
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return peak_info_vec;
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}
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