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Author SHA1 Message Date
5a051d21a1 Measurement.fromnpy(): accept sensitivity as scalar or 0-dim numpy.ndarray
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2024-09-10 13:40:47 +02:00
20 changed files with 113 additions and 490 deletions

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@ -2,7 +2,7 @@
include_directories(uldaq)
include_directories(portaudio)
add_library(lasp_device_lib OBJECT
add_library(lasp_device_lib OBJECT
lasp_daq.cpp
lasp_daqconfig.cpp
lasp_daqdata.cpp
@ -10,8 +10,12 @@ add_library(lasp_device_lib OBJECT
lasp_rtaudiodaq.cpp
lasp_streammgr.cpp
lasp_indatahandler.cpp
lasp_uldaq.cpp
uldaq/lasp_uldaq_impl.cpp
uldaq/lasp_uldaq_bufhandler.cpp
uldaq/lasp_uldaq_common.cpp
portaudio/lasp_portaudiodaq.cpp
)
)
# Callback requires certain arguments that are not used by code. This disables
# a compiler warning about it.
@ -24,9 +28,7 @@ target_include_directories(lasp_device_lib INTERFACE
${CMAKE_CURRENT_SOURCE_DIR})
if(LASP_HAS_ULDAQ)
add_subdirectory(uldaq)
target_include_directories(lasp_device_lib INTERFACE uldaq)
target_link_libraries(lasp_device_lib uldaq_backend uldaq)
target_link_libraries(lasp_device_lib uldaq)
endif()
if(LASP_HAS_RTAUDIO)
target_link_libraries(lasp_device_lib rtaudio)

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@ -1,6 +0,0 @@
add_library(uldaq_backend lasp_uldaq.cpp lasp_uldaq_bufhandler.cpp lasp_uldaq_common.cpp lasp_uldaq_impl.cpp)
target_include_directories(uldaq_backend PUBLIC ../)
target_include_directories(uldaq_backend PUBLIC ../../)
target_include_directories(uldaq_backend PUBLIC ../../dsp)
target_include_directories(uldaq_backend INTERFACE ${CMAKE_CURRENT_SOURCE_DIR})

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@ -3,8 +3,8 @@
#include "lasp_config.h"
#if LASP_HAS_ULDAQ == 1
#include "lasp_daq.h"
#include "lasp_uldaq_common.h"
#include "lasp_daq.h"
string getErrMsg(UlError err) {
string errstr;
@ -21,9 +21,11 @@ void showErr(string errstr) {
std::cerr << "***********************************************\n\n";
}
void showErr(UlError err) {
if (err != ERR_NO_ERROR) showErr(getErrMsg(err));
if (err != ERR_NO_ERROR)
showErr(getErrMsg(err));
}
void throwOnPossibleUlException(UlError err) {
if (err == ERR_NO_ERROR) {
return;

View File

@ -10,8 +10,7 @@ PowerSpectra::PowerSpectra(const us nfft, const Window::WindowType w)
: PowerSpectra(Window::create(w, nfft)) {}
PowerSpectra::PowerSpectra(const vd &window)
: nfft(window.size()), _fft(nfft), _window(window)
{
: nfft(window.size()), _fft(nfft), _window(window) {
d win_pow = arma::sum(window % window) / window.size();
@ -22,8 +21,7 @@ PowerSpectra::PowerSpectra(const vd &window)
DEBUGTRACE_PRINT(win_pow);
}
ccube PowerSpectra::compute(const dmat &input)
{
ccube PowerSpectra::compute(const dmat &input) {
/// Run very often. Silence this one.
/* DEBUGTRACE_ENTER; */
@ -36,13 +34,11 @@ ccube PowerSpectra::compute(const dmat &input)
cmat rfft = _fft.fft(input_tmp);
ccube output(rfft.n_rows, input.n_cols, input.n_cols);
for (us i = 0; i < input.n_cols; i++)
{
for (us i = 0; i < input.n_cols; i++) {
/// This one can be run in parallel without any problem. Note that it is
/// the inner loop that is run in parallel.
#pragma omp parallel for
for (us j = 0; j < input.n_cols; j++)
{
for (us j = 0; j < input.n_cols; j++) {
output.slice(j).col(i) =
_scale_fac * (rfft.col(i) % arma::conj(rfft.col(j)));
@ -56,46 +52,37 @@ ccube PowerSpectra::compute(const dmat &input)
AvPowerSpectra::AvPowerSpectra(const us nfft, const Window::WindowType w,
const d overlap_percentage,
const d time_constant_times_fs)
: _ps(nfft, w)
{
: _ps(nfft, w) {
DEBUGTRACE_ENTER;
if (overlap_percentage >= 100 || overlap_percentage < 0)
{
if (overlap_percentage >= 100 || overlap_percentage < 0) {
throw rte("Overlap percentage should be >= 0 and < 100");
}
_overlap_keep = (nfft * overlap_percentage) / 100;
DEBUGTRACE_PRINT(_overlap_keep);
if (_overlap_keep >= nfft)
{
if (_overlap_keep >= nfft) {
throw rte("Overlap is too high. Results in no jump. Please "
"choose a smaller overlap percentage or a higher nfft");
}
if (time_constant_times_fs < 0)
{
if (time_constant_times_fs < 0) {
_mode = Mode::Averaging;
}
else if (time_constant_times_fs == 0)
{
} else if (time_constant_times_fs == 0) {
_mode = Mode::Spectrogram;
}
else
{
} else {
_mode = Mode::Leaking;
_alpha = d_exp(-static_cast<d>((nfft - _overlap_keep) / time_constant_times_fs));
_alpha = d_exp(-static_cast<d>((nfft - _overlap_keep)/time_constant_times_fs));
DEBUGTRACE_PRINT(_alpha);
}
}
void AvPowerSpectra::reset()
{
void AvPowerSpectra::reset() {
_timeBuf.reset();
_est.reset();
_n_averages = 0;
n_averages=0;
}
ccube AvPowerSpectra::compute(const dmat &timedata)
{
ccube AvPowerSpectra::compute(const dmat &timedata) {
DEBUGTRACE_ENTER;
DEBUGTRACE_PRINT(timedata.n_rows);
@ -104,42 +91,32 @@ ccube AvPowerSpectra::compute(const dmat &timedata)
_timeBuf.push(timedata);
bool run_once = false;
while (_timeBuf.size() >= _ps.nfft)
{
while (_timeBuf.size() >= _ps.nfft) {
DEBUGTRACE_PRINT((int)_mode);
dmat samples = _timeBuf.pop(_ps.nfft, _overlap_keep);
switch (_mode)
{
switch (_mode) {
case (Mode::Spectrogram):
DEBUGTRACE_PRINT("Spectrogram mode");
_est = _ps.compute(samples);
break;
case (Mode::Averaging):
DEBUGTRACE_PRINT("Averaging mode");
_n_averages++;
if (_n_averages == 1)
{
n_averages++;
if (n_averages == 1) {
_est = _ps.compute(samples);
}
else
{
_est = (static_cast<d>(_n_averages - 1) / _n_averages) * _est +
_ps.compute(samples) / _n_averages;
} else {
_est = (static_cast<d>(n_averages - 1) / n_averages) * _est +
_ps.compute(samples) / n_averages;
}
break;
case (Mode::Leaking):
DEBUGTRACE_PRINT("Leaking mode");
if (arma::size(_est) == arma::size(0, 0, 0))
{
if (arma::size(_est) == arma::size(0, 0, 0)) {
_est = _ps.compute(samples);
}
else
{
} else {
_est = _alpha * _est + (1 - _alpha) * _ps.compute(samples);
}
break;
@ -151,136 +128,6 @@ ccube AvPowerSpectra::compute(const dmat &timedata)
/// Othewise, we return an empty ccube.
return run_once ? _est : ccube();
}
ccube AvPowerSpectra::get_est() const
{
return _est;
}
AvSweepPowerSpectra::AvSweepPowerSpectra(const us nfft, const Window::WindowType w,
const d overlap_percentage,
const d time_constant_times_fs)
: _nfft(nfft), _ps(nfft, w)
{
DEBUGTRACE_ENTER;
if (overlap_percentage >= 100 || overlap_percentage < 0)
{
throw rte("Overlap percentage should be >= 0 and < 100");
}
_overlap_keep = (nfft * overlap_percentage) / 100;
DEBUGTRACE_PRINT(_overlap_keep);
if (_overlap_keep >= nfft)
{
throw rte("Overlap is too high. Results in no jump. Please "
"choose a smaller overlap percentage or a higher nfft");
}
if (time_constant_times_fs < 0)
{
_mode = Mode::Averaging;
}
else if (time_constant_times_fs == 0)
{
_mode = Mode::Spectrogram;
}
else
{
_mode = Mode::Leaking;
_alpha = d_exp(-static_cast<d>((nfft - _overlap_keep) / time_constant_times_fs));
DEBUGTRACE_PRINT(_alpha);
}
}
void AvSweepPowerSpectra::reset()
{
_timeBuf.reset();
_est.reset();
_n_averages.reset();
}
ccube AvSweepPowerSpectra::compute(const dmat &timedata)
{
DEBUGTRACE_ENTER;
DEBUGTRACE_PRINT(timedata.n_rows);
DEBUGTRACE_PRINT(_ps.nfft);
_timeBuf.push(timedata);
bool run_once = false;
while (_timeBuf.size() >= _ps.nfft)
{
DEBUGTRACE_PRINT((int)_mode);
dmat samples = _timeBuf.pop(_ps.nfft, _overlap_keep);
us ncols = timedata.n_cols;
switch (_mode)
{
case (Mode::Spectrogram):
DEBUGTRACE_PRINT("Spectrogram mode");
_est = _ps.compute(samples);
break;
case (Mode::Averaging):
{
DEBUGTRACE_PRINT("Averaging mode");
ccube temp = _ps.compute(samples);
us nfreq = arma::size(temp)[0];
if (_est.size() == 0) {
// Initialize empty
_est = ccube(nfreq, ncols, ncols, arma::fill::zeros);
_n_averages = vd(nfreq, arma::fill::zeros);
}
// d threshold = arma::mean(arma::real(temp.slice(0).col(0)));
d threshold = 1e-13;
for (us f=0; f < nfreq; f++)
{
if (real(temp(f, 0, 0)) > threshold)
{
_n_averages[f]++;
if (_n_averages[f] == 1)
{
_est.row(f) = temp.row(f);
// _est.subcube(f, 0, 0, f, ncols - 1, ncols - 1) = temp.subcube(f, 0, 0, f, ncols - 1, ncols - 1);
}
else
{
_est.row(f) = (static_cast<d>(_n_averages[f] - 1) / _n_averages[f]) * _est.row(f) +
temp.row(f) / _n_averages[f];
// _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) +
// temp.subcube(f, 0, 0, f, ncols - 1, ncols - 1) / _n_averages[f];
}
}
}
}
break;
case (Mode::Leaking):
DEBUGTRACE_PRINT("Leaking mode");
if (arma::size(_est) == arma::size(0, 0, 0))
{
_est = _ps.compute(samples);
}
else
{
_est = _alpha * _est + (1 - _alpha) * _ps.compute(samples);
}
break;
} // end switch mode
run_once = true;
}
/// Return a copy of current estimator in case we have done one update.
/// Othewise, we return an empty ccube.
return run_once ? _est : ccube();
}
ccube AvSweepPowerSpectra::get_est() const
{
ccube AvPowerSpectra::get_est() const {
return _est;
}

View File

@ -81,7 +81,7 @@ class AvPowerSpectra {
Mode _mode;
d _alpha; // Only valid in case of 'Leaking'
us _n_averages = 0; // Only valid in case of 'Averaging'
us n_averages = 0; // Only valid in case of 'Averaging'
PowerSpectra _ps;
/**
@ -165,107 +165,3 @@ public:
us exactOverlapSamples() const { return _ps.nfft - _overlap_keep; }
};
/** @} */
/**
* @brief Estimate cross-power spectra using Welch' method of spectral
* estimation. The exact amount of overlap in Welch' method is rounded up to a
* certain amount of samples. This class is specifically for sweeps and will ignore
* fft blocks where the auto-power of the "reference" signal is below the average
* when in averaging mode.
*/
class AvSweepPowerSpectra {
enum class Mode {
Averaging = 0, // Averaging all time date
Leaking = 1, // Exponential weighting of an "instantaneous cps"
Spectrogram = 2 // Instantenous spectrum, no averaging
};
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; }
};
/** @} */

View File

@ -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 true
* @param mute if tre
*/
void setMute(bool mute = true) { _muted = mute; _interruption_frame_count=0; }

View File

@ -24,84 +24,60 @@ 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");
}
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];
for (us i = 0; i < nframes; i++) {
res(i) = _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);
@ -110,7 +86,7 @@ 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);
@ -118,18 +94,14 @@ 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_;
@ -138,10 +110,8 @@ 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)));
@ -150,16 +120,12 @@ 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"); */
@ -184,24 +150,18 @@ 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;
@ -209,12 +169,9 @@ 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);
@ -223,8 +180,7 @@ 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;
@ -235,16 +191,12 @@ 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;
@ -260,8 +212,7 @@ 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);
@ -285,37 +236,29 @@ 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);
}

View File

@ -58,7 +58,6 @@ 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;
@ -69,14 +68,8 @@ 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;
};
@ -88,8 +81,7 @@ class Sweep : public Periodic {
d fl_, fu_, Ts, Tq;
us index;
us flags;
vd fn_ { 1, arma::fill::zeros};
void resetImpl() override;
public:
@ -98,8 +90,6 @@ 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
*

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@ -129,29 +129,6 @@ 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,

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@ -43,22 +43,11 @@ 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);

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@ -10,11 +10,11 @@ from .lasp_cpp import *
# from .lasp_imptube import * # TwoMicImpedanceTube
from .lasp_measurement import * # Measurement, scaleBlockSens
from .lasp_octavefilter import *
from .lasp_octavefilter import * # OverallFilterBank, SosOctaveFilterBank, SosThirdOctaveFilterBank
from .lasp_slm import * # SLM, Dummy
from .lasp_record import * # RecordStatus, Recording
from .lasp_daqconfigs import *
from .lasp_measurementset import *
from .lasp_daqconfigs import * # DaqConfigurations
from .lasp_measurementset import * # MeasurementSet
# from .lasp_siggen import * # SignalType, NoiseType, SiggenMessage, SiggenData, Siggen
# from .lasp_weighcal import * # WeighCal

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@ -15,7 +15,6 @@ 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
@ -255,9 +254,9 @@ class FilterBankDesigner:
fuu = self.fu(xu)
if scale == 'lin':
freq = np.linspace(fll, fuu, npoints, dtype=LASP_NUMPY_FLOAT_TYPE)
freq = np.linspace(fll, fuu, npoints)
elif scale == 'log':
freq = np.logspace(np.log10(fll), np.log10(fuu), npoints, dtype=LASP_NUMPY_FLOAT_TYPE)
freq = np.logspace(np.log10(fll), np.log10(fuu), npoints)
else:
raise ValueError(f'Invalid scale parameter: {scale}')

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@ -7,7 +7,6 @@ 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.
@ -396,9 +395,7 @@ 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, dtype=LASP_NUMPY_FLOAT_TYPE
)
return np.linspace(start, start + N/fs, N, endpoint=False)
def getFreq(fs, nfft):
@ -409,6 +406,6 @@ 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, dtype=LASP_NUMPY_FLOAT_TYPE)
df = fs/nfft # frequency resolution
K = nfft//2+1 # number of frequency bins
return np.linspace(0, (K-1)*df, K)

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@ -5,12 +5,9 @@ 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
@ -19,28 +16,28 @@ else:
LASP_NUMPY_COMPLEX_TYPE = np.float64
def zeros(shape, dtype=float, order="F"):
if dtype is float:
def zeros(shape, dtype=float, order='F'):
if dtype == float:
return np.zeros(shape, dtype=LASP_NUMPY_FLOAT_TYPE, order=order)
elif dtype is complex:
elif dtype == 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 is float:
def ones(shape, dtype=float, order='F'):
if dtype == float:
return np.ones(shape, dtype=LASP_NUMPY_FLOAT_TYPE, order=order)
elif dtype is complex:
elif dtype == 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 is float:
def empty(shape, dtype=float, order='F'):
if dtype == float:
return np.empty(shape, dtype=LASP_NUMPY_FLOAT_TYPE, order=order)
elif dtype is complex:
elif dtype == complex:
return np.empty(shape, dtype=LASP_NUMPY_COMPLEX_TYPE, order=order)
else:
raise RuntimeError(f"Unknown dtype: {dtype}")

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@ -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, AvSweepPowerSpectra
from .lasp_cpp import Window, DaqChannel, AvPowerSpectra
from typing import List
from functools import lru_cache
from .lasp_config import ones
@ -77,9 +77,9 @@ class MeasurementType(Enum):
Measurement flags related to the measurement. Stored as bit flags in the measurement file. This is for possible changes in the API later.
"""
# Not specific measurement type
# Not specific measurement type
NotSpecific = 0
# Measurement serves as an insertion loss reference measurement
ILReference = 1 << 0
@ -814,11 +814,9 @@ class Measurement:
channels = list(range(self.nchannels))
nchannels = len(channels)
# aps = AvPowerSpectra(nfft, window, overlap)
aps = AvSweepPowerSpectra(nfft, window, overlap)
aps = AvPowerSpectra(nfft, window, overlap)
freq = getFreq(self.samplerate, nfft)
for data in self.iterData(channels, **kwargs):
CS = aps.compute(data)
@ -1007,8 +1005,7 @@ class Measurement:
# Convert range to [-1, 1]
# TODO: this is wrong for float data where full scale > 1
sensone = np.ones(data.shape[1])
sensone = np.ones_like(self.sensitivity)
data = scaleBlockSens(data, sensone)
if dtype == "int16" or dtype == "int32":
@ -1159,11 +1156,8 @@ class Measurement:
if data.ndim != 2:
data = data[:, np.newaxis]
try:
len(sensitivity)
except:
raise ValueError("Sensitivity should be given as array-like data type")
sensitivity = np.asarray(sensitivity)
if not (isinstance(sensitivity, np.ndarray) and sensitivity.ndim >= 1):
sensitivity = np.asarray(sensitivity)[np.newaxis]
nchannels = data.shape[1]
if nchannels != sensitivity.shape[0]:

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@ -11,7 +11,6 @@ __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
@ -47,7 +46,7 @@ class OverallFilterBank:
Ncur = data.shape[0]
tend = tstart + Ncur / self.fs
t = np.linspace(tstart, tend, Ncur, endpoint=False, dtype=LASP_NUMPY_FLOAT_TYPE)
t = np.linspace(tstart, tend, Ncur, endpoint=False)
self.N += Ncur
output["Overall"] = {"t": t, "data": data, "x": 0}
@ -115,7 +114,7 @@ class SosFilterBank:
Ncur = data.shape[0]
tend = tstart + Ncur / self.fs
t = np.linspace(tstart, tend, Ncur, endpoint=False, dtype=LASP_NUMPY_FLOAT_TYPE)
t = np.linspace(tstart, tend, Ncur, endpoint=False)
self.N += Ncur
for i, x in enumerate(self.xs):

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@ -4,15 +4,14 @@
Sound level meter implementation
@author: J.A. de Jong - ASCEE
"""
from .lasp_cpp import cppSLM
from .lasp_config import empty, LASP_NUMPY_FLOAT_TYPE
from .lasp_config import empty
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:
@ -90,24 +89,24 @@ 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:

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@ -7,7 +7,6 @@ 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
@ -40,7 +39,7 @@ class WeighCal:
self.calfile = calfile
# Frequencies used for the filter design
freq_design = np.linspace(0, 17e3, 3000, dtype=LASP_NUMPY_FLOAT_TYPE)
freq_design = np.linspace(0, 17e3, 3000)
freq_design[-1] = fs/2
# Objective function for the frequency response
@ -141,7 +140,6 @@ 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]),