Compare commits
7 Commits
Author | SHA1 | Date | |
---|---|---|---|
bfb23ad698 | |||
a986a6b9cd | |||
9caf5fe387 | |||
a38eca47f3 | |||
509f165ecb | |||
67bd7e6c9d | |||
047269df78 |
@ -10,12 +10,8 @@ add_library(lasp_device_lib OBJECT
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lasp_rtaudiodaq.cpp
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lasp_streammgr.cpp
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lasp_indatahandler.cpp
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lasp_uldaq.cpp
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uldaq/lasp_uldaq_impl.cpp
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uldaq/lasp_uldaq_bufhandler.cpp
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uldaq/lasp_uldaq_common.cpp
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portaudio/lasp_portaudiodaq.cpp
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)
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)
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# Callback requires certain arguments that are not used by code. This disables
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# a compiler warning about it.
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@ -28,7 +24,9 @@ target_include_directories(lasp_device_lib INTERFACE
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${CMAKE_CURRENT_SOURCE_DIR})
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if(LASP_HAS_ULDAQ)
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target_link_libraries(lasp_device_lib uldaq)
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add_subdirectory(uldaq)
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target_include_directories(lasp_device_lib INTERFACE uldaq)
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target_link_libraries(lasp_device_lib uldaq_backend uldaq)
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endif()
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if(LASP_HAS_RTAUDIO)
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target_link_libraries(lasp_device_lib rtaudio)
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6
cpp_src/device/uldaq/CMakeLists.txt
Normal file
6
cpp_src/device/uldaq/CMakeLists.txt
Normal file
@ -0,0 +1,6 @@
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add_library(uldaq_backend lasp_uldaq.cpp lasp_uldaq_bufhandler.cpp lasp_uldaq_common.cpp lasp_uldaq_impl.cpp)
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target_include_directories(uldaq_backend PUBLIC ../)
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target_include_directories(uldaq_backend PUBLIC ../../)
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target_include_directories(uldaq_backend PUBLIC ../../dsp)
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target_include_directories(uldaq_backend INTERFACE ${CMAKE_CURRENT_SOURCE_DIR})
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@ -3,8 +3,8 @@
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#include "lasp_config.h"
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#if LASP_HAS_ULDAQ == 1
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#include "lasp_uldaq_common.h"
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#include "lasp_daq.h"
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#include "lasp_uldaq_common.h"
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string getErrMsg(UlError err) {
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string errstr;
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@ -21,11 +21,9 @@ void showErr(string errstr) {
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std::cerr << "***********************************************\n\n";
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}
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void showErr(UlError err) {
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if (err != ERR_NO_ERROR)
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showErr(getErrMsg(err));
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if (err != ERR_NO_ERROR) showErr(getErrMsg(err));
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}
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void throwOnPossibleUlException(UlError err) {
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if (err == ERR_NO_ERROR) {
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return;
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@ -10,7 +10,8 @@ PowerSpectra::PowerSpectra(const us nfft, const Window::WindowType w)
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: PowerSpectra(Window::create(w, nfft)) {}
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PowerSpectra::PowerSpectra(const vd &window)
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: nfft(window.size()), _fft(nfft), _window(window) {
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: nfft(window.size()), _fft(nfft), _window(window)
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{
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d win_pow = arma::sum(window % window) / window.size();
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@ -21,7 +22,8 @@ PowerSpectra::PowerSpectra(const vd &window)
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DEBUGTRACE_PRINT(win_pow);
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}
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ccube PowerSpectra::compute(const dmat &input) {
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ccube PowerSpectra::compute(const dmat &input)
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{
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/// Run very often. Silence this one.
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/* DEBUGTRACE_ENTER; */
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@ -34,11 +36,13 @@ ccube PowerSpectra::compute(const dmat &input) {
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cmat rfft = _fft.fft(input_tmp);
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ccube output(rfft.n_rows, input.n_cols, input.n_cols);
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for (us i = 0; i < input.n_cols; i++) {
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for (us i = 0; i < input.n_cols; i++)
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{
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/// This one can be run in parallel without any problem. Note that it is
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/// the inner loop that is run in parallel.
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#pragma omp parallel for
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for (us j = 0; j < input.n_cols; j++) {
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for (us j = 0; j < input.n_cols; j++)
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{
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output.slice(j).col(i) =
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_scale_fac * (rfft.col(i) % arma::conj(rfft.col(j)));
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@ -52,37 +56,46 @@ ccube PowerSpectra::compute(const dmat &input) {
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AvPowerSpectra::AvPowerSpectra(const us nfft, const Window::WindowType w,
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const d overlap_percentage,
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const d time_constant_times_fs)
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: _ps(nfft, w) {
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: _ps(nfft, w)
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{
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DEBUGTRACE_ENTER;
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if (overlap_percentage >= 100 || overlap_percentage < 0) {
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if (overlap_percentage >= 100 || overlap_percentage < 0)
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{
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throw rte("Overlap percentage should be >= 0 and < 100");
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}
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_overlap_keep = (nfft * overlap_percentage) / 100;
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DEBUGTRACE_PRINT(_overlap_keep);
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if (_overlap_keep >= nfft) {
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if (_overlap_keep >= nfft)
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{
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throw rte("Overlap is too high. Results in no jump. Please "
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"choose a smaller overlap percentage or a higher nfft");
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}
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if (time_constant_times_fs < 0) {
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if (time_constant_times_fs < 0)
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{
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_mode = Mode::Averaging;
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} else if (time_constant_times_fs == 0) {
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}
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else if (time_constant_times_fs == 0)
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{
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_mode = Mode::Spectrogram;
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} else {
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}
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else
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{
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_mode = Mode::Leaking;
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_alpha = d_exp(-static_cast<d>((nfft - _overlap_keep)/time_constant_times_fs));
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_alpha = d_exp(-static_cast<d>((nfft - _overlap_keep) / time_constant_times_fs));
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DEBUGTRACE_PRINT(_alpha);
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}
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}
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void AvPowerSpectra::reset() {
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void AvPowerSpectra::reset()
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{
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_timeBuf.reset();
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_est.reset();
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n_averages=0;
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_n_averages = 0;
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}
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ccube AvPowerSpectra::compute(const dmat &timedata) {
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ccube AvPowerSpectra::compute(const dmat &timedata)
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{
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DEBUGTRACE_ENTER;
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DEBUGTRACE_PRINT(timedata.n_rows);
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@ -91,32 +104,42 @@ ccube AvPowerSpectra::compute(const dmat &timedata) {
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_timeBuf.push(timedata);
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bool run_once = false;
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while (_timeBuf.size() >= _ps.nfft) {
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while (_timeBuf.size() >= _ps.nfft)
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{
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DEBUGTRACE_PRINT((int)_mode);
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dmat samples = _timeBuf.pop(_ps.nfft, _overlap_keep);
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switch (_mode) {
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switch (_mode)
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{
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case (Mode::Spectrogram):
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DEBUGTRACE_PRINT("Spectrogram mode");
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_est = _ps.compute(samples);
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break;
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case (Mode::Averaging):
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DEBUGTRACE_PRINT("Averaging mode");
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n_averages++;
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if (n_averages == 1) {
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_n_averages++;
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if (_n_averages == 1)
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{
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_est = _ps.compute(samples);
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} else {
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_est = (static_cast<d>(n_averages - 1) / n_averages) * _est +
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_ps.compute(samples) / n_averages;
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}
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else
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{
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_est = (static_cast<d>(_n_averages - 1) / _n_averages) * _est +
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_ps.compute(samples) / _n_averages;
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}
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break;
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case (Mode::Leaking):
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DEBUGTRACE_PRINT("Leaking mode");
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if (arma::size(_est) == arma::size(0, 0, 0)) {
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if (arma::size(_est) == arma::size(0, 0, 0))
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{
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_est = _ps.compute(samples);
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} else {
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}
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else
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{
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_est = _alpha * _est + (1 - _alpha) * _ps.compute(samples);
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}
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break;
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@ -128,6 +151,136 @@ ccube AvPowerSpectra::compute(const dmat &timedata) {
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/// Othewise, we return an empty ccube.
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return run_once ? _est : ccube();
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}
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ccube AvPowerSpectra::get_est() const {
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ccube AvPowerSpectra::get_est() const
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{
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return _est;
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}
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AvSweepPowerSpectra::AvSweepPowerSpectra(const us nfft, const Window::WindowType w,
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const d overlap_percentage,
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const d time_constant_times_fs)
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: _nfft(nfft), _ps(nfft, w)
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{
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DEBUGTRACE_ENTER;
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if (overlap_percentage >= 100 || overlap_percentage < 0)
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{
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throw rte("Overlap percentage should be >= 0 and < 100");
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}
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_overlap_keep = (nfft * overlap_percentage) / 100;
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DEBUGTRACE_PRINT(_overlap_keep);
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if (_overlap_keep >= nfft)
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{
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throw rte("Overlap is too high. Results in no jump. Please "
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"choose a smaller overlap percentage or a higher nfft");
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}
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if (time_constant_times_fs < 0)
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{
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_mode = Mode::Averaging;
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}
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else if (time_constant_times_fs == 0)
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{
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_mode = Mode::Spectrogram;
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}
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else
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{
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_mode = Mode::Leaking;
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_alpha = d_exp(-static_cast<d>((nfft - _overlap_keep) / time_constant_times_fs));
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DEBUGTRACE_PRINT(_alpha);
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}
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}
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void AvSweepPowerSpectra::reset()
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{
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_timeBuf.reset();
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_est.reset();
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_n_averages.reset();
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}
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ccube AvSweepPowerSpectra::compute(const dmat &timedata)
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{
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DEBUGTRACE_ENTER;
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DEBUGTRACE_PRINT(timedata.n_rows);
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DEBUGTRACE_PRINT(_ps.nfft);
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_timeBuf.push(timedata);
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bool run_once = false;
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while (_timeBuf.size() >= _ps.nfft)
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{
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DEBUGTRACE_PRINT((int)_mode);
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dmat samples = _timeBuf.pop(_ps.nfft, _overlap_keep);
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us ncols = timedata.n_cols;
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switch (_mode)
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{
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case (Mode::Spectrogram):
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DEBUGTRACE_PRINT("Spectrogram mode");
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_est = _ps.compute(samples);
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break;
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case (Mode::Averaging):
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{
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DEBUGTRACE_PRINT("Averaging mode");
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ccube temp = _ps.compute(samples);
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us nfreq = arma::size(temp)[0];
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if (_est.size() == 0) {
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// Initialize empty
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_est = ccube(nfreq, ncols, ncols, arma::fill::zeros);
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_n_averages = vd(nfreq, arma::fill::zeros);
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}
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// d threshold = arma::mean(arma::real(temp.slice(0).col(0)));
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d threshold = 1e-13;
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for (us f=0; f < nfreq; f++)
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{
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if (real(temp(f, 0, 0)) > threshold)
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{
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_n_averages[f]++;
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if (_n_averages[f] == 1)
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{
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_est.row(f) = temp.row(f);
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// _est.subcube(f, 0, 0, f, ncols - 1, ncols - 1) = temp.subcube(f, 0, 0, f, ncols - 1, ncols - 1);
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}
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else
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{
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_est.row(f) = (static_cast<d>(_n_averages[f] - 1) / _n_averages[f]) * _est.row(f) +
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temp.row(f) / _n_averages[f];
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// _est.subcube(f, 0, 0, f, ncols - 1, ncols - 1) = (static_cast<d>(_n_averages[f] - 1) / _n_averages[f]) * _est.subcube(f, 0, 0, f, ncols - 1, ncols - 1) +
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// temp.subcube(f, 0, 0, f, ncols - 1, ncols - 1) / _n_averages[f];
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}
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}
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}
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}
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break;
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case (Mode::Leaking):
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DEBUGTRACE_PRINT("Leaking mode");
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if (arma::size(_est) == arma::size(0, 0, 0))
|
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{
|
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_est = _ps.compute(samples);
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}
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else
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{
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_est = _alpha * _est + (1 - _alpha) * _ps.compute(samples);
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}
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break;
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} // end switch mode
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run_once = true;
|
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}
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/// Return a copy of current estimator in case we have done one update.
|
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/// Othewise, we return an empty ccube.
|
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return run_once ? _est : ccube();
|
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}
|
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|
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ccube AvSweepPowerSpectra::get_est() const
|
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{
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return _est;
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}
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|
@ -81,7 +81,7 @@ class AvPowerSpectra {
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Mode _mode;
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d _alpha; // Only valid in case of 'Leaking'
|
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us n_averages = 0; // Only valid in case of 'Averaging'
|
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us _n_averages = 0; // Only valid in case of 'Averaging'
|
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|
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PowerSpectra _ps;
|
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/**
|
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@ -165,3 +165,107 @@ public:
|
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us exactOverlapSamples() const { return _ps.nfft - _overlap_keep; }
|
||||
};
|
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/** @} */
|
||||
|
||||
|
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/**
|
||||
* @brief Estimate cross-power spectra using Welch' method of spectral
|
||||
* estimation. The exact amount of overlap in Welch' method is rounded up to a
|
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* certain amount of samples. This class is specifically for sweeps and will ignore
|
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* fft blocks where the auto-power of the "reference" signal is below the average
|
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* when in averaging mode.
|
||||
*/
|
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class AvSweepPowerSpectra {
|
||||
|
||||
enum class Mode {
|
||||
Averaging = 0, // Averaging all time date
|
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Leaking = 1, // Exponential weighting of an "instantaneous cps"
|
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Spectrogram = 2 // Instantenous spectrum, no averaging
|
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};
|
||||
|
||||
Mode _mode;
|
||||
d _alpha; // Only valid in case of 'Leaking'
|
||||
us _nfft;
|
||||
vd _n_averages { 1, arma::fill::zeros}; // Only valid in case of 'Averaging'
|
||||
|
||||
PowerSpectra _ps;
|
||||
/**
|
||||
* @brief Current estimate of cross-spectral density
|
||||
*/
|
||||
ccube _est;
|
||||
|
||||
/**
|
||||
* @brief Buffer of storage of time data.
|
||||
*/
|
||||
TimeBuffer _timeBuf;
|
||||
/**
|
||||
* @brief The amount of samples to keep in the overlap
|
||||
*/
|
||||
us _overlap_keep;
|
||||
|
||||
public:
|
||||
/**
|
||||
* @brief Initalize averaged power spectra computer. If a time constant is
|
||||
* given > 0, it is used in a kind of exponential weighting.
|
||||
*
|
||||
* @param nfft The fft length
|
||||
* @param w The window type.
|
||||
* @param overlap_percentage A number 0 < overlap_percentage <= 100. It
|
||||
* determines the amount of overlap used in Welch' method. A typical value is
|
||||
* 50 %, i.e. 50.
|
||||
* @param fs_tau Value should either be < 0, indicating that the
|
||||
* estimate is averages over all time data.
|
||||
* For a value = 0 the instantaneous power spectrum is returned, which can be
|
||||
* interpreted as the spectrogram. For a value > 0 a exponential forgetting is
|
||||
* used, where the value is used as the time constant such that the decay
|
||||
* follows approximately the trend exp(-n/fs_tau), where n is the
|
||||
* sample number in the power spectra. To choose 'fast' time weighting, set
|
||||
* time_constant to the value of fs*0.125, where fs denotes the sampling
|
||||
* frequency.
|
||||
**/
|
||||
AvSweepPowerSpectra(const us nfft = 2048,
|
||||
const Window::WindowType w = Window::WindowType::Hann,
|
||||
const d overlap_percentage = 50.,
|
||||
const d fs_tau = -1);
|
||||
|
||||
AvSweepPowerSpectra(const AvSweepPowerSpectra &) = delete;
|
||||
AvSweepPowerSpectra &operator=(const AvSweepPowerSpectra &) = delete;
|
||||
|
||||
/**
|
||||
* @brief Reset to empty state. Clears the time buffer and sets estimator to
|
||||
* empty.
|
||||
*/
|
||||
void reset();
|
||||
|
||||
/**
|
||||
* @brief Compute an update of the power spectra based on given time data.
|
||||
* Note that the number of channels is determined from the first time this
|
||||
* function is called. If a later call has an incompatible number of
|
||||
* channels, a runtime error is thrown.
|
||||
*
|
||||
* @param timedata
|
||||
*
|
||||
* @return a copy of the latest estimate of the power spectra. an
|
||||
* update is only given if the amount of new time data is enough to compute a
|
||||
* new estimate. if no new estimate is available, it returns an empty ccube.
|
||||
* Note that the latest available estimate can be obtained using get_est().
|
||||
* */
|
||||
ccube compute(const dmat &timedata);
|
||||
|
||||
/**
|
||||
* @brief Returns the latest estimate of cps (cross-power spectra.
|
||||
*
|
||||
* @return a copy of the latest estimate of the power spectra. an
|
||||
* update is only given if the amount of new time data is enough to compute a
|
||||
* new estimate. If no estimate is available, it returns an empty ccube.
|
||||
* */
|
||||
ccube get_est() const;
|
||||
|
||||
/**
|
||||
* @brief The overlap is rounded to a certain amount of time samples. This
|
||||
* function returns that value.
|
||||
*
|
||||
* @return The amount of samples in overlapping.
|
||||
*/
|
||||
us exactOverlapSamples() const { return _ps.nfft - _overlap_keep; }
|
||||
};
|
||||
/** @} */
|
||||
|
@ -73,7 +73,7 @@ public:
|
||||
* @brief Mute the signal. Passes through the DC offset. No lock is hold. If
|
||||
* it just works one block later, than that is just the case.
|
||||
*
|
||||
* @param mute if tre
|
||||
* @param mute if true
|
||||
*/
|
||||
void setMute(bool mute = true) { _muted = mute; _interruption_frame_count=0; }
|
||||
|
||||
|
@ -24,60 +24,84 @@ DEBUGTRACE_VARIABLES;
|
||||
|
||||
Noise::Noise(){DEBUGTRACE_ENTER}
|
||||
|
||||
vd Noise::genSignalUnscaled(us nframes) {
|
||||
vd Noise::genSignalUnscaled(us nframes)
|
||||
{
|
||||
return arma::randn<vd>(nframes);
|
||||
}
|
||||
void Noise::resetImpl() {}
|
||||
|
||||
Sine::Sine(const d freq) : omg(2 * arma::datum::pi * freq) { DEBUGTRACE_ENTER; }
|
||||
|
||||
vd Sine::genSignalUnscaled(const us nframes) {
|
||||
vd Sine::genSignalUnscaled(const us nframes)
|
||||
{
|
||||
/* DEBUGTRACE_ENTER; */
|
||||
slock lck(_mtx);
|
||||
const d pi = arma::datum::pi;
|
||||
vd phase_vec =
|
||||
arma::linspace(phase, phase + omg * (nframes - 1) / _fs, nframes);
|
||||
phase += omg * nframes / _fs;
|
||||
while (phase > 2 * arma::datum::pi) {
|
||||
while (phase > 2 * arma::datum::pi)
|
||||
{
|
||||
phase -= 2 * pi;
|
||||
}
|
||||
return arma::sin(phase_vec);
|
||||
}
|
||||
|
||||
vd Periodic::genSignalUnscaled(const us nframes) {
|
||||
vd Periodic::genSignalUnscaled(const us nframes)
|
||||
{
|
||||
vd res(nframes);
|
||||
slock lck(_mtx);
|
||||
if (_signal.size() == 0) {
|
||||
if (_signal.size() == 0)
|
||||
{
|
||||
throw rte("No signal defined while calling");
|
||||
}
|
||||
for (us i = 0; i < nframes; i++) {
|
||||
res(i) = _signal[_cur_pos];
|
||||
if (_signal.size() != A_.size())
|
||||
{
|
||||
std::cout << "Seq size: " << _signal.size() << ", A size: " << A_.size() << "\n";
|
||||
throw rte("Sequence and amplitude envelopes have different lengths");
|
||||
}
|
||||
for (us i = 0; i < nframes; i++)
|
||||
{
|
||||
res(i) = A_[_cur_pos] * _signal[_cur_pos];
|
||||
_cur_pos++;
|
||||
_cur_pos %= _signal.size();
|
||||
}
|
||||
return res;
|
||||
}
|
||||
|
||||
void Periodic::setA(const vd &A)
|
||||
{
|
||||
A_ = A;
|
||||
}
|
||||
|
||||
Sweep::Sweep(const d fl, const d fu, const d Ts, const d Tq, const us flags)
|
||||
: fl_(fl), fu_(fu), Ts(Ts), Tq(Tq), flags(flags) {
|
||||
if (fl <= 0 || fu < fl || Ts <= 0) {
|
||||
: fl_(fl), fu_(fu), Ts(Ts), Tq(Tq), flags(flags)
|
||||
{
|
||||
if (fl <= 0 || fu < fl || Ts <= 0)
|
||||
{
|
||||
throw rte("Invalid sweep parameters");
|
||||
}
|
||||
if ((flags & ForwardSweep) && (flags & BackwardSweep)) {
|
||||
if ((flags & ForwardSweep) && (flags & BackwardSweep))
|
||||
{
|
||||
throw rte(
|
||||
"Both forward and backward sweep flag set. Please only set either one "
|
||||
"or none for a continuous sweep");
|
||||
}
|
||||
if ((flags & LinearSweep) && (flags & LogSweep)) {
|
||||
if ((flags & LinearSweep) && (flags & LogSweep))
|
||||
{
|
||||
throw rte(
|
||||
"Both logsweep and linear sweep flag set. Please only set either one.");
|
||||
}
|
||||
if (!((flags & LinearSweep) || (flags & LogSweep))) {
|
||||
if (!((flags & LinearSweep) || (flags & LogSweep)))
|
||||
{
|
||||
throw rte("Either LinearSweep or LogSweep should be given as flag");
|
||||
}
|
||||
|
||||
resetImpl();
|
||||
}
|
||||
|
||||
void Sweep::resetImpl() {
|
||||
void Sweep::resetImpl()
|
||||
{
|
||||
DEBUGTRACE_ENTER;
|
||||
slock lck(_mtx);
|
||||
|
||||
@ -86,7 +110,7 @@ void Sweep::resetImpl() {
|
||||
bool forward_sweep = flags & ForwardSweep;
|
||||
bool backward_sweep = flags & BackwardSweep;
|
||||
|
||||
const d Dt = 1 / _fs; // Deltat
|
||||
const d Dt = 1 / _fs; // Deltat
|
||||
|
||||
// Estimate N, the number of samples in the sweep part (non-quiescent part):
|
||||
const us Ns = (us)(Ts * _fs);
|
||||
@ -94,14 +118,18 @@ void Sweep::resetImpl() {
|
||||
const us N = Ns + Nq;
|
||||
|
||||
_signal = vd(N, arma::fill::zeros);
|
||||
fn_ = vd(N, arma::fill::zeros);
|
||||
index = 0;
|
||||
|
||||
d fl, fu;
|
||||
/* Swap fl and fu for a backward sweep */
|
||||
if (backward_sweep) {
|
||||
if (backward_sweep)
|
||||
{
|
||||
fu = fl_;
|
||||
fl = fu_;
|
||||
} else {
|
||||
}
|
||||
else
|
||||
{
|
||||
/* Case of continuous sweep, or forward sweep */
|
||||
fl = fl_;
|
||||
fu = fu_;
|
||||
@ -110,8 +138,10 @@ void Sweep::resetImpl() {
|
||||
d phase = 0;
|
||||
|
||||
/* Linear sweep */
|
||||
if (flags & LinearSweep) {
|
||||
if (forward_sweep || backward_sweep) {
|
||||
if (flags & LinearSweep)
|
||||
{
|
||||
if (forward_sweep || backward_sweep)
|
||||
{
|
||||
/* Forward or backward sweep */
|
||||
/* TRACE(15, "Forward or backward sweep"); */
|
||||
us K = (us)(Dt * (fl * Ns + 0.5 * (Ns - 1) * (fu - fl)));
|
||||
@ -120,12 +150,16 @@ void Sweep::resetImpl() {
|
||||
/* iVARTRACE(15, K); */
|
||||
/* dVARTRACE(15, eps); */
|
||||
|
||||
for (us n = 0; n < Ns; n++) {
|
||||
for (us n = 0; n < Ns; n++)
|
||||
{
|
||||
_signal(n) = d_sin(phase);
|
||||
d fn = fl + ((d)n) / Ns * (fu + eps - fl);
|
||||
fn_(n) = fn;
|
||||
phase += 2 * arma::datum::pi * Dt * fn;
|
||||
}
|
||||
} else {
|
||||
}
|
||||
else
|
||||
{
|
||||
/* Continous sweep */
|
||||
/* TRACE(15, "continuous sweep"); */
|
||||
|
||||
@ -150,18 +184,24 @@ void Sweep::resetImpl() {
|
||||
/* dVARTRACE(15, eps); */
|
||||
d phase = 0;
|
||||
|
||||
for (us n = 0; n <= Ns; n++) {
|
||||
for (us n = 0; n <= Ns; n++)
|
||||
{
|
||||
/* iVARTRACE(17, n); */
|
||||
if (n < N) {
|
||||
if (n < N)
|
||||
{
|
||||
_signal[n] = d_sin(phase);
|
||||
}
|
||||
|
||||
d fn;
|
||||
if (n <= Nf) {
|
||||
if (n <= Nf)
|
||||
{
|
||||
fn = fl + ((d)n) / Nf * (fu - fl);
|
||||
} else {
|
||||
}
|
||||
else
|
||||
{
|
||||
fn = fu - ((d)n - Nf) / Nb * (fu + eps - fl);
|
||||
}
|
||||
fn_(n) = fn;
|
||||
/* dbgassert(fn >= 0, "BUG"); */
|
||||
|
||||
phase += 2 * number_pi * Dt * fn;
|
||||
@ -169,9 +209,12 @@ void Sweep::resetImpl() {
|
||||
/* This should be a very small number!! */
|
||||
/* dVARTRACE(15, phase); */
|
||||
}
|
||||
} else if (flags & LogSweep) {
|
||||
}
|
||||
else if (flags & LogSweep)
|
||||
{
|
||||
DEBUGTRACE_PRINT("Log sweep");
|
||||
if (forward_sweep || backward_sweep) {
|
||||
if (forward_sweep || backward_sweep)
|
||||
{
|
||||
/* Forward or backward sweep */
|
||||
DEBUGTRACE_PRINT("Forward or backward sweep");
|
||||
d k1 = (fu / fl);
|
||||
@ -180,7 +223,8 @@ void Sweep::resetImpl() {
|
||||
|
||||
/* Iterate k to the right solution */
|
||||
d E;
|
||||
for (us iter = 0; iter < 10; iter++) {
|
||||
for (us iter = 0; iter < 10; iter++)
|
||||
{
|
||||
E = 1 + K / (Dt * fl) * (d_pow(k, 1.0 / Ns) - 1) - k;
|
||||
d dEdk = K / (Dt * fl) * d_pow(k, 1.0 / Ns) / (Ns * k) - 1;
|
||||
k -= E / dEdk;
|
||||
@ -191,12 +235,16 @@ void Sweep::resetImpl() {
|
||||
DEBUGTRACE_PRINT(k);
|
||||
DEBUGTRACE_PRINT(E);
|
||||
|
||||
for (us n = 0; n < Ns; n++) {
|
||||
for (us n = 0; n < Ns; n++)
|
||||
{
|
||||
_signal[n] = d_sin(phase);
|
||||
d fn = fl * d_pow(k, ((d)n) / Ns);
|
||||
fn_(n) = fn;
|
||||
phase += 2 * number_pi * Dt * fn;
|
||||
}
|
||||
} else {
|
||||
}
|
||||
else
|
||||
{
|
||||
DEBUGTRACE_PRINT("Continuous sweep");
|
||||
|
||||
const us Nf = Ns / 2;
|
||||
@ -212,7 +260,8 @@ void Sweep::resetImpl() {
|
||||
|
||||
/* Newton iterations to converge k to the value such that the sweep is
|
||||
* continuous */
|
||||
for (us iter = 0; iter < NITER_NEWTON; iter++) {
|
||||
for (us iter = 0; iter < NITER_NEWTON; iter++)
|
||||
{
|
||||
E = (k - 1) / (d_pow(k, 1.0 / Nf) - 1) +
|
||||
(k - 1) / (1 - d_pow(k, -1.0 / Nb)) - K / Dt / fl;
|
||||
DEBUGTRACE_PRINT(E);
|
||||
@ -236,29 +285,37 @@ void Sweep::resetImpl() {
|
||||
DEBUGTRACE_PRINT(k);
|
||||
DEBUGTRACE_PRINT(E);
|
||||
|
||||
for (us n = 0; n <= Ns; n++) {
|
||||
for (us n = 0; n <= Ns; n++)
|
||||
{
|
||||
/* iVARTRACE(17, n); */
|
||||
if (n < Ns) {
|
||||
if (n < Ns)
|
||||
{
|
||||
_signal[n] = d_sin(phase);
|
||||
}
|
||||
|
||||
d fn;
|
||||
if (n <= Nf) {
|
||||
if (n <= Nf)
|
||||
{
|
||||
fn = fl * d_pow(k, ((d)n) / Nf);
|
||||
} else {
|
||||
}
|
||||
else
|
||||
{
|
||||
fn = fl * k * d_pow(1 / k, ((d)n - Nf) / Nb);
|
||||
}
|
||||
fn_(n) = fn;
|
||||
/* dbgassert(fn >= 0, "BUG"); */
|
||||
|
||||
phase += 2 * number_pi * Dt * fn;
|
||||
while (phase > 2 * number_pi) phase -= 2 * number_pi;
|
||||
while (phase > 2 * number_pi)
|
||||
phase -= 2 * number_pi;
|
||||
/* dVARTRACE(17, phase); */
|
||||
}
|
||||
/* This should be a very small number!! */
|
||||
DEBUGTRACE_PRINT(phase);
|
||||
}
|
||||
} // End of log sweep
|
||||
else {
|
||||
} // End of log sweep
|
||||
else
|
||||
{
|
||||
// Either log or linear sweep had to be given as flags.
|
||||
assert(false);
|
||||
}
|
||||
|
@ -58,6 +58,7 @@ class Sine : public Siggen {
|
||||
* periodic as the frequency can be any floating point value.
|
||||
*/
|
||||
class Periodic: public Siggen {
|
||||
|
||||
protected:
|
||||
vd _signal { 1, arma::fill::zeros};
|
||||
us _cur_pos = 0;
|
||||
@ -68,8 +69,14 @@ class Periodic: public Siggen {
|
||||
* @return As stated above
|
||||
*/
|
||||
vd getSequence() const { return _signal; }
|
||||
vd A_ { 1, arma::fill::ones};
|
||||
|
||||
void setA(const vd& A);
|
||||
|
||||
virtual vd genSignalUnscaled(const us nframes) override final;
|
||||
|
||||
vd getA() const { return A_; }
|
||||
|
||||
~Periodic() = default;
|
||||
|
||||
};
|
||||
@ -81,6 +88,7 @@ class Sweep : public Periodic {
|
||||
d fl_, fu_, Ts, Tq;
|
||||
us index;
|
||||
us flags;
|
||||
vd fn_ { 1, arma::fill::zeros};
|
||||
|
||||
void resetImpl() override;
|
||||
|
||||
@ -90,6 +98,8 @@ class Sweep : public Periodic {
|
||||
static constexpr int LinearSweep = 1 << 2;
|
||||
static constexpr int LogSweep = 1 << 3;
|
||||
|
||||
vd getfn() const { return fn_; }
|
||||
|
||||
/**
|
||||
* Create a sweep signal
|
||||
*
|
||||
|
@ -129,6 +129,29 @@ void init_dsp(py::module &m) {
|
||||
return CubeToNpy<c>(est);
|
||||
});
|
||||
|
||||
/// AvSweepPowerSpectra
|
||||
py::class_<AvSweepPowerSpectra> asps(m, "AvSweepPowerSpectra");
|
||||
asps.def(py::init<const us, const Window::WindowType, const d, const d>(),
|
||||
py::arg("nfft") = 2048,
|
||||
py::arg("windowType") = Window::WindowType::Hann,
|
||||
py::arg("overlap_percentage") = 50.0,
|
||||
py::arg("time_constant") = -1);
|
||||
|
||||
asps.def("compute", [](AvSweepPowerSpectra &asps, dpyarray timedata) {
|
||||
std::optional<ccube> res;
|
||||
dmat timedata_mat = NpyToMat<d, false>(timedata);
|
||||
{
|
||||
py::gil_scoped_release release;
|
||||
res = asps.compute(timedata_mat);
|
||||
}
|
||||
|
||||
return CubeToNpy<c>(res.value_or(ccube(0, 0, 0)));
|
||||
});
|
||||
asps.def("get_est", [](const AvSweepPowerSpectra &sps) {
|
||||
ccube est = sps.get_est();
|
||||
return CubeToNpy<c>(est);
|
||||
});
|
||||
|
||||
py::class_<SLM> slm(m, "cppSLM");
|
||||
|
||||
slm.def_static("fromBiquads", [](const d fs, const d Lref, const us ds,
|
||||
|
@ -43,11 +43,22 @@ void init_siggen(py::module &m) {
|
||||
|
||||
py::class_<Periodic, std::shared_ptr<Periodic>> periodic(m, "Periodic",
|
||||
siggen);
|
||||
periodic.def("setA",
|
||||
[](Periodic &p, const dpyarray A) {
|
||||
p.setA(NpyToCol<d, false>(A));
|
||||
});
|
||||
|
||||
periodic.def("getSequence",
|
||||
[](const Sweep &s) { return ColToNpy<d>(s.getSequence()); });
|
||||
|
||||
periodic.def("getA",
|
||||
[](const Sweep &s) { return ColToNpy<d>(s.getA()); });
|
||||
|
||||
|
||||
py::class_<Sweep, std::shared_ptr<Sweep>> sweep(m, "Sweep", periodic);
|
||||
sweep.def(py::init<const d, const d, const d, const d, const us>());
|
||||
sweep.def("getfn",
|
||||
[](const Sweep &s) { return ColToNpy<d>(s.getfn()); });
|
||||
sweep.def_readonly_static("ForwardSweep", &Sweep::ForwardSweep);
|
||||
sweep.def_readonly_static("BackwardSweep", &Sweep::BackwardSweep);
|
||||
sweep.def_readonly_static("LinearSweep", &Sweep::LinearSweep);
|
||||
|
@ -15,6 +15,7 @@ import warnings
|
||||
import numpy as np
|
||||
# For designing second-order sections
|
||||
from scipy.signal import butter
|
||||
from ..lasp_config import LASP_NUMPY_FLOAT_TYPE
|
||||
|
||||
from .fir_design import bandpass_fir_design
|
||||
from .fir_design import freqResponse as firFreqResponse
|
||||
@ -254,9 +255,9 @@ class FilterBankDesigner:
|
||||
fuu = self.fu(xu)
|
||||
|
||||
if scale == 'lin':
|
||||
freq = np.linspace(fll, fuu, npoints)
|
||||
freq = np.linspace(fll, fuu, npoints, dtype=LASP_NUMPY_FLOAT_TYPE)
|
||||
elif scale == 'log':
|
||||
freq = np.logspace(np.log10(fll), np.log10(fuu), npoints)
|
||||
freq = np.logspace(np.log10(fll), np.log10(fuu), npoints, dtype=LASP_NUMPY_FLOAT_TYPE)
|
||||
else:
|
||||
raise ValueError(f'Invalid scale parameter: {scale}')
|
||||
|
||||
|
@ -7,6 +7,7 @@ from dataclasses import dataclass
|
||||
from dataclasses_json import dataclass_json
|
||||
from enum import Enum, unique, auto
|
||||
from .lasp_cpp import DaqChannel
|
||||
from .lasp_config import LASP_NUMPY_FLOAT_TYPE
|
||||
|
||||
"""
|
||||
Common definitions used throughout the code.
|
||||
@ -395,7 +396,9 @@ def getTime(fs, N, start=0):
|
||||
start: Optional start ofset in number of samples
|
||||
"""
|
||||
assert N > 0 and fs > 0
|
||||
return np.linspace(start, start + N/fs, N, endpoint=False)
|
||||
return np.linspace(
|
||||
start, start + N / fs, N, endpoint=False, dtype=LASP_NUMPY_FLOAT_TYPE
|
||||
)
|
||||
|
||||
|
||||
def getFreq(fs, nfft):
|
||||
@ -406,6 +409,6 @@ def getFreq(fs, nfft):
|
||||
fs: Sampling frequency [Hz]
|
||||
nfft: Fft length (int)
|
||||
"""
|
||||
df = fs/nfft # frequency resolution
|
||||
K = nfft//2+1 # number of frequency bins
|
||||
return np.linspace(0, (K-1)*df, K)
|
||||
df = fs / nfft # frequency resolution
|
||||
K = nfft // 2 + 1 # number of frequency bins
|
||||
return np.linspace(0, (K - 1) * df, K, dtype=LASP_NUMPY_FLOAT_TYPE)
|
||||
|
@ -5,9 +5,12 @@ Author: J.A. de Jong - ASCEE
|
||||
|
||||
Description: LASP configuration
|
||||
"""
|
||||
|
||||
import numpy as np
|
||||
from .lasp_cpp import LASP_DOUBLE_PRECISION
|
||||
|
||||
__all__ = ["zeros", "ones", "empty", "LASP_NUMPY_FLOAT_TYPE", "LASP_NUMPY_COMPLEX_TYPE"]
|
||||
|
||||
if LASP_DOUBLE_PRECISION:
|
||||
LASP_NUMPY_FLOAT_TYPE = np.float64
|
||||
LASP_NUMPY_COMPLEX_TYPE = np.complex128
|
||||
@ -16,28 +19,28 @@ else:
|
||||
LASP_NUMPY_COMPLEX_TYPE = np.float64
|
||||
|
||||
|
||||
def zeros(shape, dtype=float, order='F'):
|
||||
if dtype == float:
|
||||
def zeros(shape, dtype=float, order="F"):
|
||||
if dtype is float:
|
||||
return np.zeros(shape, dtype=LASP_NUMPY_FLOAT_TYPE, order=order)
|
||||
elif dtype == complex:
|
||||
elif dtype is complex:
|
||||
return np.zeros(shape, dtype=LASP_NUMPY_COMPLEX_TYPE, order=order)
|
||||
else:
|
||||
raise RuntimeError(f"Unknown dtype: {dtype}")
|
||||
|
||||
|
||||
def ones(shape, dtype=float, order='F'):
|
||||
if dtype == float:
|
||||
def ones(shape, dtype=float, order="F"):
|
||||
if dtype is float:
|
||||
return np.ones(shape, dtype=LASP_NUMPY_FLOAT_TYPE, order=order)
|
||||
elif dtype == complex:
|
||||
elif dtype is complex:
|
||||
return np.ones(shape, dtype=LASP_NUMPY_COMPLEX_TYPE, order=order)
|
||||
else:
|
||||
raise RuntimeError(f"Unknown dtype: {dtype}")
|
||||
|
||||
def empty(shape, dtype=float, order='F'):
|
||||
if dtype == float:
|
||||
|
||||
def empty(shape, dtype=float, order="F"):
|
||||
if dtype is float:
|
||||
return np.empty(shape, dtype=LASP_NUMPY_FLOAT_TYPE, order=order)
|
||||
elif dtype == complex:
|
||||
elif dtype is complex:
|
||||
return np.empty(shape, dtype=LASP_NUMPY_COMPLEX_TYPE, order=order)
|
||||
else:
|
||||
raise RuntimeError(f"Unknown dtype: {dtype}")
|
||||
|
||||
|
@ -15,7 +15,7 @@ from scipy.io import wavfile
|
||||
import os, time, wave, logging
|
||||
from .lasp_common import SIQtys, Qty, getFreq
|
||||
from .lasp_version import LASP_VERSION_MAJOR, LASP_VERSION_MINOR
|
||||
from .lasp_cpp import Window, DaqChannel, AvPowerSpectra
|
||||
from .lasp_cpp import Window, DaqChannel, AvPowerSpectra, AvSweepPowerSpectra
|
||||
from typing import List
|
||||
from functools import lru_cache
|
||||
from .lasp_config import ones
|
||||
@ -814,7 +814,9 @@ class Measurement:
|
||||
channels = list(range(self.nchannels))
|
||||
|
||||
nchannels = len(channels)
|
||||
aps = AvPowerSpectra(nfft, window, overlap)
|
||||
|
||||
# aps = AvPowerSpectra(nfft, window, overlap)
|
||||
aps = AvSweepPowerSpectra(nfft, window, overlap)
|
||||
freq = getFreq(self.samplerate, nfft)
|
||||
|
||||
for data in self.iterData(channels, **kwargs):
|
||||
@ -1005,7 +1007,8 @@ class Measurement:
|
||||
|
||||
# Convert range to [-1, 1]
|
||||
# TODO: this is wrong for float data where full scale > 1
|
||||
sensone = np.ones_like(self.sensitivity)
|
||||
sensone = np.ones(data.shape[1])
|
||||
|
||||
data = scaleBlockSens(data, sensone)
|
||||
|
||||
if dtype == "int16" or dtype == "int32":
|
||||
|
@ -11,6 +11,7 @@ __all__ = ["OverallFilterBank", "SosOctaveFilterBank", "SosThirdOctaveFilterBank
|
||||
|
||||
from .filter.filterbank_design import OctaveBankDesigner, ThirdOctaveBankDesigner
|
||||
from .lasp_cpp import BiquadBank
|
||||
from .lasp_config import empty, LASP_NUMPY_FLOAT_TYPE
|
||||
import numpy as np
|
||||
|
||||
|
||||
@ -46,7 +47,7 @@ class OverallFilterBank:
|
||||
Ncur = data.shape[0]
|
||||
tend = tstart + Ncur / self.fs
|
||||
|
||||
t = np.linspace(tstart, tend, Ncur, endpoint=False)
|
||||
t = np.linspace(tstart, tend, Ncur, endpoint=False, dtype=LASP_NUMPY_FLOAT_TYPE)
|
||||
self.N += Ncur
|
||||
|
||||
output["Overall"] = {"t": t, "data": data, "x": 0}
|
||||
@ -114,7 +115,7 @@ class SosFilterBank:
|
||||
Ncur = data.shape[0]
|
||||
tend = tstart + Ncur / self.fs
|
||||
|
||||
t = np.linspace(tstart, tend, Ncur, endpoint=False)
|
||||
t = np.linspace(tstart, tend, Ncur, endpoint=False, dtype=LASP_NUMPY_FLOAT_TYPE)
|
||||
self.N += Ncur
|
||||
|
||||
for i, x in enumerate(self.xs):
|
||||
|
@ -4,14 +4,15 @@
|
||||
Sound level meter implementation
|
||||
@author: J.A. de Jong - ASCEE
|
||||
"""
|
||||
|
||||
from .lasp_cpp import cppSLM
|
||||
from .lasp_config import empty
|
||||
from .lasp_config import empty, LASP_NUMPY_FLOAT_TYPE
|
||||
import numpy as np
|
||||
from .lasp_common import (TimeWeighting, FreqWeighting, P_REF)
|
||||
from .lasp_common import TimeWeighting, FreqWeighting, P_REF
|
||||
from .filter import SPLFilterDesigner
|
||||
import logging
|
||||
|
||||
__all__ = ['SLM', 'Dummy']
|
||||
__all__ = ["SLM", "Dummy"]
|
||||
|
||||
|
||||
class Dummy:
|
||||
@ -89,24 +90,24 @@ class SLM:
|
||||
elif fw == FreqWeighting.Z:
|
||||
prefilter = None
|
||||
else:
|
||||
raise ValueError(f'Not implemented prefilter {fw}')
|
||||
raise ValueError(f"Not implemented prefilter {fw}")
|
||||
|
||||
# 'Probe' size of filter coefficients
|
||||
self.nom_txt = []
|
||||
|
||||
# This is a bit of a hack, as the 5 is hard-encoded here, but should in
|
||||
# fact be coming from somewhere else..
|
||||
sos_overall = np.array([1, 0, 0, 1, 0, 0]*5, dtype=float)
|
||||
sos_overall = np.array([1, 0, 0, 1, 0, 0] * 5, dtype=float)
|
||||
|
||||
if fbdesigner is not None:
|
||||
assert fbdesigner.fs == fs
|
||||
sos_firstx = fbdesigner.createSOSFilter(self.xs[0]).flatten()
|
||||
self.nom_txt.append(fbdesigner.nominal_txt(self.xs[0]))
|
||||
sos = empty((sos_firstx.size, nfilters), dtype=float, order='C')
|
||||
sos = empty((sos_firstx.size, nfilters), dtype=float, order="C")
|
||||
sos[:, 0] = sos_firstx
|
||||
|
||||
for i, x in enumerate(self.xs[1:]):
|
||||
sos[:, i+1] = fbdesigner.createSOSFilter(x).flatten()
|
||||
sos[:, i + 1] = fbdesigner.createSOSFilter(x).flatten()
|
||||
self.nom_txt.append(fbdesigner.nominal_txt(x))
|
||||
|
||||
if include_overall:
|
||||
|
@ -7,6 +7,7 @@ Weighting and calibration filter in one
|
||||
from .lasp_common import FreqWeighting
|
||||
from .filter import SPLFilterDesigner
|
||||
from lasp.lasp_config import ones, empty
|
||||
from ..lasp_config import LASP_NUMPY_FLOAT_TYPE
|
||||
from .wrappers import FilterBank
|
||||
import numpy as np
|
||||
|
||||
@ -39,7 +40,7 @@ class WeighCal:
|
||||
self.calfile = calfile
|
||||
|
||||
# Frequencies used for the filter design
|
||||
freq_design = np.linspace(0, 17e3, 3000)
|
||||
freq_design = np.linspace(0, 17e3, 3000, dtype=LASP_NUMPY_FLOAT_TYPE)
|
||||
freq_design[-1] = fs/2
|
||||
|
||||
# Objective function for the frequency response
|
||||
@ -140,6 +141,7 @@ class WeighCal:
|
||||
"""
|
||||
Returns the frequency response of the designed FIR filter
|
||||
"""
|
||||
raise RuntimeError('This code bugs. TODO: Re-implement?')
|
||||
if freq is None:
|
||||
freq = np.logspace(1, np.log10(self.fs/2), 500)
|
||||
return (freq, frp(self.fs, freq, self._firs[chan]),
|
||||
|
Loading…
Reference in New Issue
Block a user