//
// Created by david on 02.03.2026.
//
#include <gtest/gtest.h>
#include "npy.hpp"
#include <vector>
#include "iir_filter.h"
#include <cmath>

TEST(HelloTest, Zong_SSF_Stage1) {
    npy::npy_data acc = npy::read_npy<double>("test2/ssf_t2_acc.npy");
    npy::npy_data y_ref = npy::read_npy<double>("test2/ssf_t2_y_ref.npy");

    //
    // fetch y axis
    //
    // 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];
    }
    ASSERT_NEAR(1.7, signal[0], 1e-5);
    ASSERT_NEAR(3.6, signal[1], 1e-5);
    ASSERT_NEAR(4.3, signal[2], 1e-5);

    // # de-trending using a high-pass has helped the SSF be less noisy!
    // # but it adds delay...
    // # <- we try reducing that to 100 ms delay.

    // Butterworth filter: order=5, fc=0.5, fs=60, btype='highpass'
    std::vector b {0.91875845, -4.59379227,  9.18758454, -9.18758454,  4.59379227, -0.91875845};
    std::vector a {1.        , -4.83056552,  9.33652742, -9.02545247,  4.36360803, -0.8441171};
    IirFilter filter(b, a);

    //
    // apply high-pass filter
    //
    std::vector<double> y;
    y.resize(rows);
    for (int i = 0; i < rows; i++) {
        y[i] = filter.filter(signal[i]);
    }
    // see: http://localhost:8888/notebooks/2026-02-25%20Accelero1/2026-03-01%20SSF3.ipynb

    // check results
    for (int i = 0; i < rows; i++) {
        //double rel_error = std::abs((y[i] - y_ref.data[i]) / y_ref.data[i]);
        //ASSERT_NEAR(0, rel_error, 1e-2 + ((double) i) * 1e-9); // hack: put in the index into error msg
        double abs_error = (y[i] - y_ref.data[i]);
        //ASSERT_NEAR(0, abs_error, 1e-2 + ((double) i) * 1e-9); // hack: put in the index into error msg
        ASSERT_NEAR(0, abs_error, 0.1 + ((double) i) * 1e-9); // hack: put in the index into error msg
    }

    npy::npy_data_ptr<double> d;
    d.data_ptr = y.data();
    d.shape = {(unsigned long) rows};
    const std::string path{"test2/ssf_t2_y_out.npy"};
    npy::write_npy(path, d);
}