libpasada/google-tests/test_helpers.cpp

//
// Created by david on 11.03.2026.
//

#include "test_helpers.h"

void npy_save(std::string path, std::vector<double>& x) {
    npy::npy_data_ptr<double> d;
    d.data_ptr = x.data();
    d.shape = {(unsigned long) x.size()};
    npy::write_npy(path, d);
}
void npy_save(std::string path, std::vector<bool>& x) {
    npy::npy_data_ptr<int> d;
    std::vector<int> xx(x.begin(), x.end());
    d.data_ptr = xx.data();
    d.shape = {(unsigned long) x.size()};
    npy::write_npy(path, d);
}

std::vector<double> fetch_y_axis(npy::npy_data<double>& acc) {
    // TODO: later on, we should use a vector projection towards gravity
    std::vector<double> signal;
    const size_t rows_real = acc.shape[0];
#if DEBUG_IIR == 1
    const size_t rows = 5;
#else
    const size_t rows = acc.shape[0];
#endif
    int stride = 3;
    int offset = 1; // [x,y,z] per row - fetch y
    signal.resize(rows);
    if (acc.fortran_order) {
        stride = 1;
        offset = (int) rows_real;
    }
    /*
    std::cout << "is_fortran=" << acc.fortran_order << std::endl;
    for (size_t i = 0; i < 10; i++) {
        std::cout << "acc.data[" << i << "]=" << acc.data[i] << std::endl;
    }
    */
    for (int i = 0; i < rows; i++) {
        signal[i] = acc.data[i * stride + offset];
    }
    return signal;
}

DebugSsfStepDetectorThreshold::DebugSsfStepDetectorThreshold(size_t len_refr) : SsfStepDetector(len_refr) {}
double DebugSsfStepDetectorThreshold::filter(double val) {
    this->SsfStepDetector::filter(val);
    return peek_threshold();
}