// // Created by david on 02.03.2026. // #include #include "npy.hpp" #include #include "iir_filter.h" #include "ssf_filter.h" #include "test_helpers.h" #include #include #define FPS 60 #define MAX_BPM 300 TEST(HelloTest, Zong_SSF_Stage1) { npy::npy_data acc = npy::read_npy("test2/ssf_t2_acc.npy"); npy::npy_data y_ref = npy::read_npy("test2/ssf_t2_y_ref.npy"); std::vector signal = fetch_y_axis(acc); const size_t N = signal.size(); 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. #if (FPS != 60) #error "FPS must currently be 60, as highpass taps are pre-computed for that value" #endif // 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 y; y.resize(N); for (int i = 0; i < N; 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 < N; 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 d; d.data_ptr = y.data(); d.shape = {(unsigned long) N}; const std::string path{"test2/ssf_t2_y_out.npy"}; npy::write_npy(path, d); } TEST(HelloTest, Filter_Delta_U) { Filt f_delta_u(2, 0, 0, std::vector {1.0, -1.0}); std::vector x { 1.0, 3.0, 2.0 }; std::vector y_ref { 1.0, 2.0, -1.0 }; std::vector y; y.resize(x.size()); for (int i = 0; i < x.size(); i++) { y[i] = f_delta_u.filter(x[i]); } for (int i = 0; i < x.size(); i++) { ASSERT_NEAR(y_ref[i], y[i], 1e-5); } } // NOTE: later SSF must be fed -u, not u TEST(HelloTest, Filter_SSF) { SsfFilter f_ssf(3); std::vector x { 1.0, 3.0, 2.0, 5.0, 1.0, 1.5 }; // du { 1.0, 2.0, -1.0, 3.0, -4.0, 0.5 } // duc { 1.0, 2.0, 0.0, 3.0, 0.0, 0.5 } // ssf { 1.0, 3.0, 3.0, 5.0, 3.0, 3.5 } std::vector ssf_ref { 1.0, 3.0, 3.0, 5.0, 3.0, 3.5 }; std::vector ssf; ssf.resize(x.size()); for (int i = 0; i < x.size(); i++) { ssf[i] = f_ssf.filter(x[i]); } for (int i = 0; i < x.size(); i++) { ASSERT_NEAR(ssf_ref[i], ssf[i], 1e-5); } } TEST(HelloTest, Zong_SSF_Stage2) { npy::npy_data acc = npy::read_npy("test2/ssf_t2_acc.npy"); std::vector signal = fetch_y_axis(acc); #if (FPS != 60) #error "FPS must currently be 60, as highpass taps are pre-computed for that value" #endif // 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); // Stage 1: high-pass auto y = apply_filter(filter, signal); Filt f_neg(1, 0, 0, std::vector {-1.0}); auto y_neg = apply_filter(f_neg, y); // Stage 2: sum slope function const size_t upslope_width = 4; SsfFilter f_ssf(upslope_width); auto ssf = apply_filter(f_ssf, y_neg); npy_save("test2/ssf_t2_ssf.npy", ssf); } TEST(HelloTest, Zong_SSF_Stage3) { npy::npy_data acc = npy::read_npy("test2/ssf_t2_acc.npy"); std::vector signal = fetch_y_axis(acc); #if (FPS != 60) #error "FPS must currently be 60, as highpass taps are pre-computed for that value" #endif // 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); //std::cerr << "before stage 1" << std::endl; // Stage 1: high-pass auto y = apply_filter(filter, signal); Filt f_neg(1, 0, 0, std::vector {-1.0}); auto y_neg = apply_filter(f_neg, y); //std::cerr << "before stage 2" << std::endl; // Stage 2: sum slope function const size_t upslope_width = 4; SsfFilter f_ssf(upslope_width); auto ssf = apply_filter(f_ssf, y_neg); //std::cerr << "before stage 3" << std::endl; // Stage 3: threshold detection const size_t len_refr = (size_t) (FPS / (MAX_BPM / 60)); DebugSsfStepDetectorThreshold f_ssd_thr(len_refr); auto ssf_threshold = apply_filter(f_ssd_thr, ssf); //std::cerr << "before writing results 1 and doing step detection" << std::endl; npy_save("test2/ssf_t2_ssf_threshold.npy", ssf_threshold); SsfStepDetector f_ssd(len_refr); auto steps = apply_filter(f_ssd, ssf); //std::cerr << "before writing results 2" << std::endl; npy_save("test2/ssf_t2_steps.npy", steps); }