snip.cpp

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#include <algorithm>
#include <cmath>
 
#include <Eigen/Eigen>
 
#include "snip.h"
 
namespace sablib {
 
const std::vector<double>
BaselineSnip(
    const std::vector<double> & y, const unsigned int m, const bool decreasing,
    const SnipPreprocess preprocess, const unsigned int loop
)
{
    if(y.size() == 0) {
        throw std::invalid_argument("BaselineSnip(): the length of y is zero.");
    }
 
    if(y.size() < 2 * m) {
        throw std::invalid_argument("BaselineSnip(): the length of y is shorter than 2 * m.");
    }
 
    if(m == 0) {
        throw std::invalid_argument("BaselineSnip(): m is zero.");
    }
 
    if(loop == 0) {
        throw std::invalid_argument("BaselineSnip(): loop is zero.");
    }
 
    Eigen::VectorXd yy;
    unsigned int n = (unsigned int)y.size();
 
    switch(preprocess) {
    case SnipPreprocess::LL:
        yy = Eigen::VectorXd::Map(y.data(), n).unaryExpr(
            [](const double x) {
                return x > 0 ? std::log(std::log(x + 1) + 1) : 0;
            }
        );
        break;
    case SnipPreprocess::LLS:
        yy = Eigen::VectorXd::Map(y.data(), n).unaryExpr(
            [](const double x) {
                return x > 0 ? std::log(std::log(std::sqrt(x + 1) + 1) + 1) : 0;
            }
        );
        break;
    default:
        yy = Eigen::VectorXd::Map(y.data(), n);
    }
 
    std::vector<unsigned int> index;
 
    for(unsigned int i = 0; i < m; i++){
        index.emplace_back(decreasing ? (m - i) : (i + 1));
    }
 
    Eigen::VectorXd v = yy;
 
    for(unsigned int i = 0; i < loop; i++) {
        for(auto j : index) {
            Eigen::VectorXd v_prev = v;
 
            for(unsigned int k = j; k < n - j; k++) {
                double ave = (v_prev(k + j) + v_prev(k - j)) / 2;
                v(k) = std::min(v_prev(k), ave);
            }
        }
    }
 
    std::vector<double> result(v.size());
 
    switch(preprocess) {
    case SnipPreprocess::LL:
        Eigen::VectorXd::Map(result.data(), result.size()) = v.unaryExpr(
            [](const double x) {
                return std::exp(std::exp(x) - 1) - 1;
            }
        );
        break;
    case SnipPreprocess::LLS:
        Eigen::VectorXd::Map(result.data(), result.size()) = v.unaryExpr(
            [](const double x) {
                double t = std::exp(std::exp(x) - 1) - 1;
                return t * t  - 1;
            }
        );
        break;
    default:
        Eigen::VectorXd::Map(result.data(), result.size()) = v;
    }
 
    return result;
}
 
}; // namespace sablib