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aoSystem.cpp
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/** \file aoSystem.cpp
* \author Jared R. Males ([email protected])
* \brief Application class and main definition for the aoSystem app.
* \ingroup files
*
*/
//***********************************************************************//
// Copyright 2018-2021 Jared R. Males ([email protected])
//
// This file is part of aoSystem.
//
// aoSystem is free software: you can redistribute it and/or modify
// it under the terms of the GNU General Public License as published by
// the Free Software Foundation, either version 3 of the License, or
// (at your option) any later version.
//
// aoSystem is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU General Public License
// along with aoSystem. If not, see <http://www.gnu.org/licenses/>.
//***********************************************************************//
#include <iostream>
#include <fstream>
#include <Eigen/Dense>
#include <mx/ioutils/fits/fitsFile.hpp>
#include <mx/math/constants.hpp>
#include <mx/math/func/airyPattern.hpp>
#include <mx/app/application.hpp>
#include <mx/math/ft/fftwEnvironment.hpp>
using namespace mx::math;
#include <mx/ao/analysis/aoSystem.hpp>
#include <mx/ao/analysis/aoPSDs.hpp>
#include <mx/ao/analysis/aoWFS.hpp>
#include <mx/ao/analysis/varmapToImage.hpp>
#include <mx/ao/analysis/fourierTemporalPSD.hpp>
/* git version header, generated by gengithead.sh using mxlib make system */
#include "aoSystem_git_version.h"
using namespace mx::app;
///
/**
* Star Magnitudes:
* - if <b>starMag</b> alone is set, then results are provided for just this one star magnitude.
* - if <b>starMags</b>, a vector, is set, then many results are provided for each magnitude. E.g. <b>--mode</b>=ErrorBudget will produce a table.
*/
template <typename _realT>
class mxAOSystem_app : public mx::app::application
{
public:
typedef _realT realT; ///< Real floating point type for calculations
typedef Eigen::Array<realT, -1, -1> imageT; ///< The image type
typedef mx::AO::analysis::aoSystem<realT, mx::AO::analysis::vonKarmanSpectrum<realT>, std::ostream> m_aosysT; ///< The AO system type.
/// Default constructor
mxAOSystem_app();
/// Desctructor
~mxAOSystem_app();
protected:
m_aosysT m_aosys; ///< The ao system.
mx::AO::analysis::wfs<realT> idealWFS; ///< An ideal WFS
mx::AO::analysis::pywfsUnmod<realT> unmodPyWFS; ///< An unmodulated Pyramid WFS
mx::AO::analysis::pywfsModAsymptotic<realT> asympModPyWFS; ///< A modulated Pyramid WFS in its asymptotic limit
realT lam_0;
bool m_dumpSetup{true};
std::string m_setupOutName{"aoSystem_setup.txt"};
std::string m_mode{"C2Var"};
std::string wfeUnits;
bool m_strehlOG {1};
std::vector<realT> m_starMags;
realT m_dfreq{0.1};
realT m_fmax{0};
realT k_m;
realT k_n;
std::string gridDir; ///< The directory for writing the grid of PSDs.
std::string subDir; ///< The sub-directory of gridDir where to write the analysis results.
realT m_gfixed{0};
int lpNc {0}; ///< Number of linear predictor coefficients. If <= 1 then not used.
realT lpRegPrec {2}; ///< The initial precision for the LP regularization algorithm. Normal value is 2. Higher is faster. Decrease if getting stuck in local minima.
bool m_uncontrolledLifetimes{false}; ///< Whether or not lifetimes are calcualated for uncontrolled modes.
int m_lifetimeTrials{0}; ///< Number of trials to use for calculating speckle lifetimes. If 0, lifetimes are not calcualted.
bool m_writePSDs{false}; ///< Flag controlling whether output temporal PSDs are written to disk or not.
bool m_writeXfer{false}; ///< Flag controlling whether output transfer functions are written to disk or not.
virtual void setupConfig();
virtual void loadConfig();
virtual int execute();
int C_MapCon(const std::string &mapFile,
imageT &map);
int C0Var();
int C0Con();
int C1Var();
int C1Con();
int C2Var();
int C2Con();
int C3Var();
int C3Con();
int C4Var();
int C4Con();
int C5Var();
int C5Con();
int C6Var();
int C6Con();
int C7Var();
int C7Con();
int CVarAll();
int CConAll();
int ErrorBudget();
int temporalPSD();
int temporalPSDGrid();
int temporalPSDGridAnalyze();
/// Output current parameters to a stream
/** Outputs a formatted list of all current parameters.
*
*/
template <typename iosT>
iosT &dumpSetup(iosT &ios /**< [in] a std::ostream-like stream. */);
};
template <typename realT>
mxAOSystem_app<realT>::mxAOSystem_app()
{
m_configPathGlobal_env = "MXAOSYSTEM_GLOBAL_CONFIG";
m_configPathLocal = "aoSystem.conf";
m_requireConfigPathLocal = false;
lam_0 = 0;
// m_aosys.wfsBeta( idealWFS );
wfeUnits = "rad";
m_aosys.loadMagAOX();
k_m = 1;
k_n = 0;
}
template <typename realT>
mxAOSystem_app<realT>::~mxAOSystem_app()
{
}
template <typename realT>
void mxAOSystem_app<realT>::setupConfig()
{
// App config
config.add("mode", "m", "mode", argType::Required, "", "mode", false, "string", "Mode of calculation: ErrorBudget, C<N>Var, C<N>Con, CVarAll, CConAll, temporalPSD, temporalPSDGrid, temporalPSDGridAnalyze");
config.add("setupOutFile", "", "setupOutFile", argType::Required, "", "setupOutFile", false, "string", "Filename for output of setup data");
config.add("wfeUnits", "", "wfeUnits", argType::Required, "", "wfeUnits", false, "string", "Units for WFE in ErrorBudget: rad or nm");
// Load a model
config.add("model", "", "model", argType::Required, "", "model", false, "string", "Model to load: Guyon2005, MagAOX, or GMagAOX");
m_aosys.setupConfig(config);
config.add("aosys.starMags", "", "aosys.starMags", argType::Required, "aosys", "starMags", false, "real vector", "A vector of star magnitudes");
config.add("aosys.strehlOG", "", "aosys.strehlOG", argType::Required, "aosys", "strehlOG", false, "bool", "Flag controlling whether Strehl is used as the optical gain in error budgets. Default true.");
// PSD Configuration
// config.add("subTipTilt" ,"", "subTipTilt", argType::Required, "PSD", "subTipTilt", false, "bool", "If set to true, the Tip/Tilt component is subtracted from the PSD.");
// config.add("scintillation" ,"", "scintillation", argType::Required, "PSD", "scintillation", false, "bool", "If set to true, then scintillation is included in the PSD.");
// config.add("component" ,"", "component", argType::Required, "PSD", "component", false, "string", "Can be phase [default], amplitude, or dispersion.");
// Temporal configuration
config.add("fmax", "", "fmax", argType::Required, "temporal", "fmax", false, "real", "Maximum temporal frequency at which to explicitly calculate PSDs. If 0 (default) this is based on highest wind peak. A -17/3 power law is used above this frequency.");
config.add("dfreq", "", "dfreq", argType::Required, "temporal", "dfreq", false, "real", "Spacing of frequencies in the analysis.");
config.add("k_m", "", "k_m", argType::Required, "temporal", "k_m", false, "real", "The spatial frequency m index.");
config.add("k_n", "", "k_n", argType::Required, "temporal", "k_n", false, "real", "The spatial frequency n index.");
config.add("gridDir", "", "gridDir", argType::Required, "temporal", "gridDir", false, "string", "The directory to store the grid of PSDs.");
config.add("subDir", "", "subDir", argType::Required, "temporal", "subDir", false, "string", "The directory to store the analysis results.");
config.add("gfixed", "", "gfixed", argType::Required, "temporal", "gfixed", false, "float", "if > 0 then this fixed gain is used in the SI.");
config.add("lpNc", "", "lpNc", argType::Required, "temporal", "lpNc", false, "int", "The number of linear prediction coefficients to use (if <= 1 ignored)");
config.add("lpRegPrec", "", "lpRegPrec", argType::Required, "temporal", "lpRegPrec", false, "int", "The initial precision for the LP regularization algorithm. Normal value is 2. Higher is faster. Decrease if getting stuck in local minima.s to use (if <= 1 ignored)");
config.add("uncontrolledLifetimes", "", "uncontrolledLifetimes", argType::Required, "temporal", "uncontrolledLifetimes", false, "bool", "If true, lifetimes are calculated for uncontrolled modes. Default is false.");
config.add("lifetimeTrials", "", "lifetimeTrials", argType::Required, "temporal", "lifetimeTrials", false, "int", "Number of trials to use for calculating speckle lifetimes. If 0, lifetimes are not calcualted.");
config.add("writePSDs", "", "writePSDs", argType::True, "temporal", "writePSDs", false, "bool", "Flag. If set then output PSDs are written to disk.");
config.add("writeXfer", "", "writeXfer", argType::True, "temporal", "writeXfer", false, "bool", "Flag. If set then output transfer functions are written to disk.");
}
template <typename realT>
void mxAOSystem_app<realT>::loadConfig()
{
std::vector<realT> vecTmp;
/**********************************************************/
/* App setup */
/**********************************************************/
config(doHelp, "help");
config(m_mode, "mode");
config(wfeUnits, "wfeUnits");
/**********************************************************/
/* Models */
/**********************************************************/
// These are called before anything else, so all parameters are modifications.
///\todo this should actually get processed as a config file, so these settings override previous configs for proper cascading. As it is now, if D is set in any config file, it will get overwritten, for instance.
std::string model;
config(model, "model");
if(model != "")
{
if(model == "Guyon2005")
m_aosys.loadGuyon2005();
else if(model == "MagAOX")
m_aosys.loadMagAOX();
else if(model == "GMagAOX")
m_aosys.loadGMagAOX();
else
{
std::cerr << "Unknown model: " << model << "\n";
doHelp = true;
return;
}
}
/**********************************************************/
/* System */
/**********************************************************/
m_aosys.loadConfig(config);
if(config.isSet("aosys.starMags"))
{
config(m_starMags, "aosys.starMags");
}
config(m_strehlOG, "aosys.strehlOG");
/**********************************************************/
/* Temporal PSDs */
/**********************************************************/
config(m_fmax, "fmax");
config(m_dfreq, "dfreq");
config(k_m, "k_m");
config(k_n, "k_n");
config(gridDir, "gridDir");
config(subDir, "subDir");
config(m_gfixed, "gfixed");
config(lpNc, "lpNc");
config(lpRegPrec, "lpRegPrec");
config(m_uncontrolledLifetimes, "uncontrolledLifetimes");
config(m_lifetimeTrials, "lifetimeTrials");
config(m_writePSDs, "writePSDs");
config(m_writeXfer, "writeXfer");
if(config.m_unusedConfigs.size() > 0)
{
std::cerr << "****************************************************\n";
std::cerr << "WARNING: unrecognized config options:\n";
for(auto it = config.m_unusedConfigs.begin(); it != config.m_unusedConfigs.end(); ++it)
{
std::cerr << " " << it->second.name;
if(config.m_sources)
std::cerr << " [" << it->second.sources[0] << "]\n";
else
std::cerr << "\n";
}
std::cerr << "****************************************************\n";
}
if(config.nonOptions.size() > 0)
{
std::cerr << "****************************************************\n";
std::cerr << "WARNING: unrecognized command line arguments\n";
}
}
template <typename realT>
int mxAOSystem_app<realT>::execute()
{
int rv;
if(m_mode == "ErrorBudget")
{
rv = ErrorBudget();
}
else if(m_mode == "C0Var")
{
rv = C0Var();
}
else if(m_mode == "C0Con")
{
rv = C0Con();
}
else if(m_mode == "C1Var")
{
rv = C1Var();
}
else if(m_mode == "C1Con")
{
rv = C1Con();
}
else if(m_mode == "C2Var")
{
rv = C2Var();
}
else if(m_mode == "C2Con")
{
rv = C2Con();
}
else if(m_mode == "C3Var")
{
rv = C3Var();
}
else if(m_mode == "C3Con")
{
rv = C3Con();
}
else if(m_mode == "C4Var")
{
rv = C4Var();
}
else if(m_mode == "C4Con")
{
rv = C4Con();
}
else if(m_mode == "C5Var")
{
rv = C5Var();
}
else if(m_mode == "C5Con")
{
rv = C5Con();
}
else if(m_mode == "C6Var")
{
rv = C6Var();
}
else if(m_mode == "C6Con")
{
rv = C6Con();
}
else if(m_mode == "C7Var")
{
rv = C7Var();
}
else if(m_mode == "C7Con")
{
rv = C7Con();
}
else if(m_mode == "CVarAll")
{
rv = CVarAll();
}
else if(m_mode == "CConAll")
{
rv = CConAll();
}
else if(m_mode == "temporalPSD")
{
rv = temporalPSD();
}
else if(m_mode == "temporalPSDGrid")
{
rv = temporalPSDGrid();
}
else if(m_mode == "temporalPSDGridAnalyze")
{
rv = temporalPSDGridAnalyze();
}
else
{
std::cerr << "Unknown mode: " << m_mode << "\n\n";
rv = -1;
}
if(m_dumpSetup)
{
std::ofstream fout;
fout.open(m_setupOutName);
dumpSetup(fout);
fout.close();
}
if(rv < 0)
{
std::cerr << "An error occurred. Please use -h or --help to get help.";
if(m_dumpSetup)
std::cerr << " Current settings written to " << m_setupOutName;
std::cerr << "\n";
}
return rv;
}
template <typename realT>
int mxAOSystem_app<realT>::C_MapCon(const std::string &mapFile,
imageT &map)
{
imageT im, psf;
psf.resize(map.rows(), map.cols());
for(int i = 0; i < psf.rows(); ++i)
{
for(int j = 0; j < psf.cols(); ++j)
{
psf(i, j) = mx::math::func::airyPattern(sqrt(pow(i - floor(.5 * psf.rows()), 2) + pow(j - floor(.5 * psf.cols()), 2)));
}
}
mx::AO::analysis::varmapToImage(im, map, psf);
for(int i = 0; i < m_aosys.fit_mn_max(); ++i)
{
std::cout << i << " " << im(m_aosys.fit_mn_max() + 1, m_aosys.fit_mn_max() + 1 + i) << "\n";
}
mx::fits::fitsFile<realT> ff;
ff.write(mapFile, im);
return 0;
}
template <typename realT>
int mxAOSystem_app<realT>::C0Var()
{
imageT map;
map.resize(m_aosys.fit_mn_max() * 2 + 1, m_aosys.fit_mn_max() * 2 + 1);
m_aosys.C0Map(map, false);
mx::fits::fitsFile<realT> ff;
ff.write("C0Var.fits", map);
for(int i = 0; i < m_aosys.fit_mn_max(); ++i)
{
std::cout << i << " " << m_aosys.C0(i, 0, false) << "\n";
}
return 0;
}
template <typename realT>
int mxAOSystem_app<realT>::C0Con()
{
imageT map;
map.resize(m_aosys.fit_mn_max() * 2 + 1, m_aosys.fit_mn_max() * 2 + 1);
m_aosys.C0Map(map, true);
C_MapCon("C0Con.fits", map);
return 0;
}
template <typename realT>
int mxAOSystem_app<realT>::C1Var()
{
imageT map;
map.resize(m_aosys.fit_mn_max() * 2 + 1, m_aosys.fit_mn_max() * 2 + 1);
m_aosys.C1Map(map, false);
mx::fits::fitsFile<realT> ff;
ff.write("C1Var.fits", map);
for(int i = 0; i < m_aosys.fit_mn_max(); ++i)
{
std::cout << i << " " << m_aosys.C1(i, 0, false) << "\n";
}
return 0;
}
template <typename realT>
int mxAOSystem_app<realT>::C1Con()
{
imageT map;
map.resize(m_aosys.fit_mn_max() * 2 + 1, m_aosys.fit_mn_max() * 2 + 1);
m_aosys.C1Map(map, true);
C_MapCon("C1Con.fits", map);
return 0;
}
template <typename realT>
int mxAOSystem_app<realT>::C2Var()
{
imageT map;
map.resize(m_aosys.fit_mn_max() * 2 + 1, m_aosys.fit_mn_max() * 2 + 1);
m_aosys.C2Map(map, false);
mx::fits::fitsFile<realT> ff;
ff.write("C2Var.fits", map);
for(int i = 0; i < m_aosys.fit_mn_max(); ++i)
{
std::cout << i << " " << m_aosys.C2(i, 0, false) << "\n";
}
return 0;
}
template <typename realT>
int mxAOSystem_app<realT>::C2Con()
{
imageT map;
map.resize(m_aosys.fit_mn_max() * 2 + 1, m_aosys.fit_mn_max() * 2 + 1);
m_aosys.C2Map(map, true);
C_MapCon("C2Con.fits", map);
return 0;
}
template <typename realT>
int mxAOSystem_app<realT>::C3Var()
{
imageT map;
map.resize(m_aosys.fit_mn_max() * 2 + 1, m_aosys.fit_mn_max() * 2 + 1);
m_aosys.C3Map(map, false);
mx::fits::fitsFile<realT> ff;
ff.write("C3Var.fits", map);
for(int i = 0; i < m_aosys.fit_mn_max(); ++i)
{
std::cout << i << " " << m_aosys.C3(i, 0, false) << "\n";
}
return 0;
}
template <typename realT>
int mxAOSystem_app<realT>::C3Con()
{
imageT map;
map.resize(m_aosys.fit_mn_max() * 2 + 1, m_aosys.fit_mn_max() * 2 + 1);
m_aosys.C3Map(map, true);
C_MapCon("C3Con.fits", map);
return 0;
}
template <typename realT>
int mxAOSystem_app<realT>::C4Var()
{
imageT map;
map.resize(m_aosys.fit_mn_max() * 2 + 1, m_aosys.fit_mn_max() * 2 + 1);
m_aosys.C4Map(map, false);
mx::fits::fitsFile<realT> ff;
ff.write("C4Var.fits", map);
for(int i = 0; i < m_aosys.fit_mn_max(); ++i)
{
std::cout << i << " " << m_aosys.C4(i, 0, false) << "\n";
}
return 0;
}
template <typename realT>
int mxAOSystem_app<realT>::C4Con()
{
imageT map;
map.resize(m_aosys.fit_mn_max() * 2 + 1, m_aosys.fit_mn_max() * 2 + 1);
m_aosys.C4Map(map, true);
C_MapCon("C4Con.fits", map);
return 0;
}
template <typename realT>
int mxAOSystem_app<realT>::C5Var()
{
imageT map;
map.resize(m_aosys.fit_mn_max() * 2 + 1, m_aosys.fit_mn_max() * 2 + 1);
m_aosys.C5Map(map, false);
mx::fits::fitsFile<realT> ff;
ff.write("C5Var.fits", map);
for(int i = 0; i < m_aosys.fit_mn_max(); ++i)
{
std::cout << i << " " << m_aosys.C5(i, 0, false) << "\n";
}
return 0;
}
template <typename realT>
int mxAOSystem_app<realT>::C5Con()
{
imageT map;
map.resize(m_aosys.fit_mn_max() * 2 + 1, m_aosys.fit_mn_max() * 2 + 1);
m_aosys.C5Map(map, true);
C_MapCon("C5Con.fits", map);
return 0;
}
template <typename realT>
int mxAOSystem_app<realT>::C6Var()
{
imageT map;
map.resize(m_aosys.fit_mn_max() * 2 + 1, m_aosys.fit_mn_max() * 2 + 1);
m_aosys.C6Map(map, false);
mx::fits::fitsFile<realT> ff;
ff.write("C6Var.fits", map);
for(int i = 0; i < m_aosys.fit_mn_max(); ++i)
{
std::cout << i << " " << m_aosys.C6(i, 0, false) << "\n";
}
return 0;
}
template <typename realT>
int mxAOSystem_app<realT>::C6Con()
{
imageT map;
map.resize(m_aosys.fit_mn_max() * 2 + 1, m_aosys.fit_mn_max() * 2 + 1);
m_aosys.C6Map(map, true);
C_MapCon("C6Con.fits", map);
return 0;
}
template <typename realT>
int mxAOSystem_app<realT>::C7Var()
{
imageT map;
map.resize(m_aosys.fit_mn_max() * 2 + 1, m_aosys.fit_mn_max() * 2 + 1);
m_aosys.C7Map(map, false);
mx::fits::fitsFile<realT> ff;
ff.write("C7Var.fits", map);
for(int i = 0; i < m_aosys.fit_mn_max(); ++i)
{
std::cout << i << " " << m_aosys.C7(i, 0, false) << "\n";
}
return 0;
}
template <typename realT>
int mxAOSystem_app<realT>::C7Con()
{
imageT map;
map.resize(m_aosys.fit_mn_max() * 2 + 1, m_aosys.fit_mn_max() * 2 + 1);
m_aosys.C7Map(map, true);
C_MapCon("C7Con.fits", map);
return 0;
}
template <typename realT>
int mxAOSystem_app<realT>::CVarAll()
{
std::cout << "# Residual Variance Profiles\n";
std::cout << "# sep[lam/d] C0 C1 C2 C3 C4 C5 C6 C7\n";
for(int i = 0; i < m_aosys.fit_mn_max(); ++i)
{
std::cout << i << " " << m_aosys.C0(i, 0, false) << " " << m_aosys.C1(i, 0, false) << " ";
std::cout << m_aosys.C2(i, 0, false) << " " << m_aosys.C3(i, 0, false) << " ";
std::cout << m_aosys.C4(i, 0, false) << " " << m_aosys.C5(i, 0, false) << " ";
std::cout << m_aosys.C6(i, 0, false) << " " << m_aosys.C7(i, 0, false) << "\n";
}
return 0;
}
template <typename realT>
int mxAOSystem_app<realT>::CConAll()
{
imageT map, im0, im1, im2, im3, im4, im5, im6, im7;
map.resize(m_aosys.fit_mn_max() * 2 + 1, m_aosys.fit_mn_max() * 2 + 1);
imageT psf;
psf.resize(map.rows(), map.cols());
for(int i = 0; i < psf.rows(); ++i)
{
for(int j = 0; j < psf.cols(); ++j)
{
psf(i, j) = mx::math::func::airyPattern(sqrt(pow(i - floor(.5 * psf.rows()), 2) + pow(j - floor(.5 * psf.cols()), 2)));
}
}
m_aosys.C0Map(map, true);
mx::AO::analysis::varmapToImage(im0, map, psf);
m_aosys.C1Map(map, true);
mx::AO::analysis::varmapToImage(im1, map, psf);
m_aosys.C2Map(map, true);
mx::AO::analysis::varmapToImage(im2, map, psf);
m_aosys.C3Map(map, true);
mx::AO::analysis::varmapToImage(im3, map, psf);
m_aosys.C4Map(map, true);
mx::AO::analysis::varmapToImage(im4, map, psf);
m_aosys.C5Map(map, true);
mx::AO::analysis::varmapToImage(im5, map, psf);
m_aosys.C6Map(map, true);
mx::AO::analysis::varmapToImage(im6, map, psf);
m_aosys.C7Map(map, true);
mx::AO::analysis::varmapToImage(im7, map, psf);
std::cout << "# Residual Contrast Profiles\n";
std::cout << "# sep[lam/d] C0 C1 C2 C3 C4 C5 C6 C7\n";
for(int i = 0; i < m_aosys.fit_mn_max(); ++i)
{
std::cout << i + 1 << " " << im0(m_aosys.fit_mn_max() + 1, m_aosys.fit_mn_max() + 1 + i) << " " << im1(m_aosys.fit_mn_max() + 1, m_aosys.fit_mn_max() + 1 + i) << " ";
std::cout << im2(m_aosys.fit_mn_max() + 1, m_aosys.fit_mn_max() + 1 + i) << " " << im3(m_aosys.fit_mn_max() + 1, m_aosys.fit_mn_max() + 1 + i) << " ";
std::cout << im4(m_aosys.fit_mn_max() + 1, m_aosys.fit_mn_max() + 1 + i) << " " << im5(m_aosys.fit_mn_max() + 1, m_aosys.fit_mn_max() + 1 + i) << " ";
std::cout << im6(m_aosys.fit_mn_max() + 1, m_aosys.fit_mn_max() + 1 + i) << " " << im7(m_aosys.fit_mn_max() + 1, m_aosys.fit_mn_max() + 1 + i) << "\n";
}
return 0;
}
template <typename realT>
int mxAOSystem_app<realT>::ErrorBudget()
{
realT units = 1;
if(wfeUnits == "nm")
{
units = m_aosys.lam_sci() / (mx::math::two_pi<realT>()) / 1e-9;
}
if(m_starMags.size() == 0)
{
m_starMags.push_back(m_aosys.starMag());
}
std::cout << "#mag\t d\t bin \t n_modes \t Measurement\t TimeDelay\t Fitting\t ChrScintOPD\t ChrIndex\t DispAnisoOPD NCP \t Strehl\n";
for(size_t i = 0; i < m_starMags.size(); ++i)
{
m_aosys.starMag(m_starMags[i]);
if(m_strehlOG)
{
// Iterative optical gain
/// \todo need upstream NCP and CP NCP and NCP NCP
realT ncp = m_aosys.ncp_wfe(); // save ncp and then set it to zero for this part.
m_aosys.ncp_wfe(0);
realT lam_sci = m_aosys.lam_sci();
m_aosys.lam_sci(m_aosys.lam_wfs());
realT S = m_aosys.strehl();
// std::cerr << S << "\n";
if(S > -1) // 0.1)
{
for(int s = 0; s < 4; ++s)
{
m_aosys.opticalGain(S);
m_aosys.optd(m_aosys.optd()); // just trigger a re-calc
S = m_aosys.strehl();
// std::cerr << S << "\n";
}
}
else
{
m_aosys.opticalGain(0.1);
}
m_aosys.lam_sci(lam_sci);
m_aosys.ncp_wfe(ncp);
}
realT S = m_aosys.strehl();
std::cout << m_starMags[i] << "\t ";
std::cout << m_aosys.d_opt() << "\t ";
std::cout << m_aosys.bin_opt() + 1 << "\t ";
std::cout << m_aosys.controlledModes().sum() << "\t";
std::cout << sqrt(m_aosys.measurementErrorTotal()) * units << "\t ";
std::cout << sqrt(m_aosys.timeDelayErrorTotal()) * units << "\t ";
std::cout << sqrt(m_aosys.fittingErrorTotal()) * units << "\t ";
std::cout << sqrt(m_aosys.chromScintOPDErrorTotal()) * units << "\t ";
std::cout << sqrt(m_aosys.chromIndexErrorTotal()) * units << "\t ";
std::cout << sqrt(m_aosys.dispAnisoOPDErrorTotal()) * units << "\t ";
std::cout << sqrt(m_aosys.ncpError()) * units << "\t ";
std::cout << S << "\n";
}
return 0;
}
template <typename realT>
int mxAOSystem_app<realT>::temporalPSD()
{
std::vector<realT> freq, psdOL, psdN, psdSI, psdLP;
mx::AO::analysis::fourierTemporalPSD<realT, m_aosysT> ftPSD;
ftPSD.m_aosys = &m_aosys;
if(m_aosys.tauWFS() <= 0)
{
std::cerr << "temporalPSD: You must set tauWFS to be > 0 to specify loop frequency.\n";
return -1;
}
if(m_dfreq <= 0)
{
std::cerr << "temporalPSD: You must set dfreq to be > 0 to specify frequency sampling.\n";
return -1;
}
realT fs = 1.0 / m_aosys.tauWFS();
mx::math::vectorScale(freq, 0.5 * fs / m_dfreq, m_dfreq, m_dfreq);
psdOL.resize(freq.size());
ftPSD.multiLayerPSD(psdOL, freq, k_m, k_n, 1, m_fmax);
// Create WFS Noise PSD
psdN.resize(freq.size());
mx::AO::analysis::wfsNoisePSD<realT>(psdN, m_aosys.beta_p(k_m, k_n), m_aosys.Fg(), (1.0 / fs), m_aosys.npix_wfs((size_t)0), m_aosys.Fbg((size_t)0), m_aosys.ron_wfs((size_t)0));
// optimize
mx::AO::analysis::clAOLinearPredictor<realT> tflp;
mx::AO::analysis::clGainOpt<realT> go_si(m_aosys.tauWFS(), m_aosys.deltaTau());
mx::AO::analysis::clGainOpt<realT> go_lp(m_aosys.tauWFS(), m_aosys.deltaTau());
go_si.f(freq);
realT gmaxSI = 0;
realT varSI;
realT goptSI = go_si.optGainOpenLoop(varSI, psdOL, psdN, gmaxSI);
// Only bother if number of coefficients is > 1.
realT goptLP = -1;
realT varLP = -1;
if(lpNc > 1)
{
go_lp.f(freq);
realT gmaxLP;
tflp.m_precision0 = lpRegPrec;
tflp.regularizeCoefficients(gmaxLP, goptLP, varLP, go_lp, psdOL, psdN, lpNc);
}
realT tauOL = 0, tauSI = 0, tauLP = 0;
if(m_lifetimeTrials > 0)
{
std::vector<realT> spfreq, sppsd;
std::vector<std::complex<realT>> ETFxn(freq.size()), NTFxn(freq.size());
mx::sigproc::psdVarMean<mx::sigproc::psdVarMeanParams<realT>> pvm;
mx::sigproc::psdVarMean<mx::sigproc::psdVarMeanParams<realT>> pvmLP;
realT splifeT = 100.0;
realT error;
realT spvar;
// Measure OL
for(size_t i = 0; i < freq.size(); ++i)
{
ETFxn[i] = 1.0;
NTFxn[i] = 0.0;
}
mx::AO::analysis::speckleAmpPSD(spfreq, sppsd, freq, psdOL, ETFxn, psdN, NTFxn, m_lifetimeTrials);
spvar = mx::sigproc::psdVar(spfreq, sppsd);
tauOL = pvm(error, spfreq, sppsd, splifeT) * (splifeT) / spvar;
if(goptSI > 0)
{
for(size_t i = 0; i < freq.size(); ++i)
{
ETFxn[i] = go_si.clETF(i, goptSI);
NTFxn[i] = go_si.clNTF(i, goptSI);
}
}
else
{
for(size_t i = 0; i < freq.size(); ++i)
{
ETFxn[i] = 1;
NTFxn[i] = 0;
}
}
mx::AO::analysis::speckleAmpPSD(spfreq, sppsd, freq, psdOL, ETFxn, psdN, NTFxn, m_lifetimeTrials);
spvar = mx::sigproc::psdVar(spfreq, sppsd);
tauSI = pvm(error, spfreq, sppsd, splifeT) * (splifeT) / spvar;
if(goptLP > 0)
{
for(size_t i = 0; i < freq.size(); ++i)
{
ETFxn[i] = go_lp.clETF(i, goptLP);
NTFxn[i] = go_lp.clNTF(i, goptLP);
}
}
else
{
for(size_t i = 0; i < freq.size(); ++i)
{
ETFxn[i] = 1;
NTFxn[i] = 0;
}
}
mx::AO::analysis::speckleAmpPSD(spfreq, sppsd, freq, psdOL, ETFxn, psdN, NTFxn, m_lifetimeTrials);
spvar = mx::sigproc::psdVar(spfreq, sppsd);
tauLP = pvmLP(error, spfreq, sppsd, splifeT) * (splifeT) / spvar;
}
dumpSetup(std::cout);
std::cout << "# aoSystem single temporal PSD\n";
std::cout << "# var OL = " << "\n";
if(m_lifetimeTrials > 0)
std::cout << "# tau OL = " << tauOL << "\n";
std::cout << "# opt-gain SI = " << goptSI << "\n";
std::cout << "# var SI = " << varSI << "\n";