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ImFusion SDK 4.3
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ImFusion SDK 4.3
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#include <ImFusion/Base/OptimizerXNES.h>
XNES optimizer. More...
Inheritance diagram for OptimizerXNES:XNES optimizer.
Public Member Functions | |
| OptimizerXNES (int n, CostFunction *cf=nullptr, const std::vector< std::string > ¶mNames={}) | |
| Constructor with dimension. | |
| ~OptimizerXNES () override | |
| Destructor. | |
| void | abort () override |
| Request to abort the optimization. | |
| void | setUpdateSpeed (double speed=0.2) |
| Set update speed, range [0 - 1.0]. Default value 0.2. Higher value increases changes in parameters but can result in premature convergence. | |
| double | updateSpeed () |
| Get current update speed. | |
| void | setPopulation (int pop=50) |
| Set population size, default value 50. Higher values create more robust results, but sacrifices speed approx. linearly (100-500 are good values). | |
| void | setInitVariances (std::vector< double > initVar) |
| Set initial standard deviations for the parameters by supplying a vector<double> of values. | |
| void | setInitVariance (double var) |
| Set the initial variance to be used in all dimensions. Use setInitVariances to set the values individually per dimension. | |
| void | setSparseMode (bool sparse=true) |
| Set the mode of the optimizer to SPARSE. | |
| void | addSparseConnection (int k, int l) |
| Add a sparse correlation when using the algorithm in SPARSE mode. | |
| void | resetSparse () |
| Remove all sparse correlations, except for the diagonal. | |
| void | setSeed (int seed) |
| Set the seed to the stochastic part of the algorithm. | |
| int | population () |
| Get the current population size. | |
| Public Member Functions inherited from Optimizer | |
| Optimizer (int n, int type, CostFunction *cf=0, const std::vector< std::string > ¶mNames={}) | |
| Constructor with dimension and optimization type. | |
| ~Optimizer () override | |
| Destructor. | |
| virtual void | setType (int val) |
| Set the optimizer type. | |
| void | setCostFunction (CostFunction *cf) |
| Set the cost function. | |
| void | setErrorFunction (ErrorFunction *ef) |
| Set an optional error function. | |
| void | setProgress (Progress *p) |
| Provide an optional progress callback. | |
| void | setProgressUpdate (bool flag) |
| Specify if a progress update shall be shown during optimization (does not apply for randomized studies) | |
| bool | progressUpdate () const |
| void | setProgressBetter (bool flag) |
| Specify if progress update should only be called if cost function has improved. | |
| bool | progressBetter () const |
| void | setProgressUpdatesDisplay (bool flag) |
| Specify if whether the Optimizer should set the Update Display flag when reporting progress. | |
| bool | progressUpdatesDisplay () const |
| void | setProgressText (const std::string &description) |
| Specify optional custom description for progress reporting (ignored if empty) | |
| const std::string & | progressText () const |
| std::string | paramName (int i) const |
| Get the name of a parameter if it has been specified, otherwise defaults to "Parameter i". | |
| void | setParamNames (const std::vector< std::string > ¶mNames) |
| Set the names of the parameters. | |
| bool | hasParamNames () const |
| True, if m_paraNames is not empty. | |
| void | setLogging (int file, int console=0) |
| Set level of detail for logging to both text file and the console. | |
| std::pair< int, int > | logging () const |
| void | setLogFilename (const std::string &filename) |
| Set a custom log file name or path (file logging has to be enabled/disabled independently with setLogging) | |
| void | setAddToStudy (bool flag) |
| Specify whether individual optimization runs should be added to the OptimizationStudy. | |
| void | repeatSelection (int n, int extra=0) |
| Reconfigures the optimizer to solve a problem with the size of n times the selection. | |
| void | setMinimize (bool flag) |
| Specify if the cost function is to be minimized or maximized. | |
| void | setScale (double scale) |
| Set an overall parameter scaling. | |
| void | setScale (const std::vector< double > scale) |
| Set an individual parameter scaling. | |
| void | setSelection (const std::vector< bool > &sel) |
| Specify that only some of the parameters should be optimized. | |
| void | setMode (Mode mode, double range=1.0, int steps=1, bool includeOrig=false) |
| Set the desired mode of operation, as well as range and steps for study or plot. | |
| virtual int | execute (double *x) |
| Execute the optimization given initial parameters of full dimensionality. Negative return values indicate an error. | |
| double | evaluate (int n, const double *x, double *dx=0) override |
| Wraps the cost function evaluation. | |
| void | shrink (const double *all, double *sel) const |
| Shrink to selected parameters and/or divide by scaling. | |
| void | expand (const double *sel, double *all) const |
| Expand to all parameters and/or multiply by scaling. | |
| void | setAbortEval (int num) |
| int | abortEval () const |
| void | setAbortTime (double sec) |
| Abort after a certain elapsed number of seconds. | |
| double | abortTime () const |
| void | setAbortFunVal (double val) |
| Abort if this function value is reached. | |
| double | abortFunVal () const |
| void | setAbortFunTol (double val) |
| Abort if change in cost function value is becomes too small. | |
| double | abortFunTol () const |
| void | setAbortParTol (double val) |
| Abort if change in parameter values becomes too small. | |
| double | abortParTol () const |
| void | setBounds (double bounds) |
| A value of zero disables the bounds. | |
| void | setBounds (double lower, double upper) |
| Set the same lower and upper bounds for all parameters. | |
| void | setBounds (const std::vector< double > &bounds) |
| Set individual symmetric bounds. | |
| void | setBounds (const std::vector< double > &lower, const std::vector< double > &upper) |
| Set individual lower and upper bounds. | |
| const std::vector< double > & | lowerBounds () const |
| const std::vector< double > & | upperBounds () const |
| int | type () const |
| Mode | mode () const |
| Return the mode of operation. | |
| bool | minimize () const |
| Return whether cost function is minimized. | |
| double | range () const |
| Return range for study or plot. | |
| int | steps () const |
| Return the number of steps for used for study or plot. | |
| bool | studyIncludeOrig () const |
| Return whether random studies shall include the original parameters. | |
| double | firstVal () const |
| Return cost function value of first evaluation. | |
| double | bestVal () const |
| Return best cost function value. | |
| double | error (int which=0) const |
| Return current value of error function. | |
| int | numEval () const |
| Return number of executed cost function evaluations. | |
| bool | isAtBounds (std::vector< int > *indicesAtBounds=nullptr) const |
| Return whether the current parameters touch the specified bounds, and their indices if a vector is passed. | |
| int | dimension () const |
| Return the total number of parameters (dimension) | |
| void | setDimension (int d) |
Sets the dimension and the number of selected parameters to d and clears the selection. | |
| int | selDim () const |
| Return number of selected parameters. | |
| const std::vector< bool > & | selection () const |
| Return the selected parameters. | |
| const std::vector< double > & | scale () const |
| Return the parameter scaling. | |
| Progress * | progress () |
| Return the progress callback. | |
| ErrorFunction * | errorFunction () |
| Return the error function pointer. | |
| bool | aborted () const |
| Return if the optimizer was aborted. | |
| float * | plotData () |
| Return plot result data. | |
| OptimizationStudy * | studyResults () const |
| Return random study result. Do not delete returned Optimization study object. It is owned by the Optimization class. | |
| bool | addToStudy () const |
| Return whether optimization runs are added to the study. | |
| const std::string & | logFilename () const |
| Return the custom log file name. | |
| Public Member Functions inherited from Configurable | |
| virtual void | configureDefaults () |
| Retrieve the properties of this object, replaces values with their defaults and sets it again. | |
| void | registerParameter (ParameterBase *param) |
| Register the given Parameter or SubProperty, so that it will be configured during configure()/configuration(). | |
| void | unregisterParameter (const ParameterBase *param) |
| Remove the given Parameter or SubProperty from the list of registered parameters. | |
| Configurable (const Configurable &rhs) | |
| Configurable (Configurable &&rhs) noexcept | |
| Configurable & | operator= (const Configurable &) |
| Configurable & | operator= (Configurable &&) noexcept |
Implements the Configurable interface | |
| void | configure (const Properties *p) override |
| Configure this object instance by de-serializing the given Properties. | |
| void | configuration (Properties *p) const override |
| Serialize the current object configuration into the given Properties object. | |
Additional Inherited Members | |
| Public Types inherited from Optimizer | |
| enum | Mode { OPT = 0 , STUDY = 1 , PLOT = 2 , EVALUATE = 3 } |
| Mode of operation when execute is called. More... | |
| Public Attributes inherited from Optimizer | |
| Signal< int, int > | signalStudyStepFinished |
| Signal emitted after each step of a random study, arguments are <current step> and <num total steps> | |
| Public Attributes inherited from Configurable | |
| Signal | signalParametersChanged |
Emitted whenever one of the registered Parameters' or SubPropertys' signalValueChanged signal was emitted. | |
| Protected Member Functions inherited from Optimizer | |
| virtual const char * | resultName (int value) const |
| Return a string describing the optimizer's return value. | |
| void | computeStats (double *pars, int n) const |
| Compute statistics on random study parameters. | |
| void | randomOptimization (double *pars) |
| Executes successive optimizations with randomized initial parameters. | |
| void | computePlot (double *pars) |
| Computes a 1D or 2D plot of selected parameters. | |
| void | logResultFile (const double *pInit, const double *pOpt) |
| Auxiliary method to write the optimization result to a file. | |
| void | logResultConsole (const double *pOpt, int result=0) |
| Auxiliary method to log the optimization result to the console. | |
| Protected Attributes inherited from Optimizer | |
| CostFunction * | m_cf = nullptr |
| Cost function instance to be optimized. | |
| ErrorFunction * | m_ef = nullptr |
| Optional error function instance. | |
| Progress * | m_progress = nullptr |
| Optional progress callback. | |
| std::unique_ptr< Progress::Task > | m_progressTask |
| progress reporting instance of execute() | |
| std::unique_ptr< Timer > | m_timer |
| Timer instance. | |
| std::unique_ptr< OptimizationStudy > | m_study |
| Results of random study. | |
| bool | m_addToStudy = false |
| Optimization study is automatically appended. | |
| int | m_dim |
| Dimensions of the optimization problem. | |
| int | m_selDim |
| Dimensions of the selected parameters. | |
| int | m_type |
| Implementation-specific optimization type. | |
| int | m_loggingF = 0 |
| Level of detail for file logging. | |
| int | m_loggingC = 0 |
| Level of detail for console logging. | |
| int | m_abortEval = 0 |
| Maximum number of cost function evaluations. | |
| double | m_abortTime = 0.0 |
| Number of seconds after which to abort. | |
| double | m_abortFunVal = 0.0 |
| Abort when this function values is reached. | |
| double | m_abortFunTol = 0.0 |
| Cost function tolerance abortion criteria. | |
| double | m_abortParTol = 0.0 |
| Parameter tolerance abortion criteria. | |
| bool | m_minimize = false |
| Shall the cost function be minimized or maximized. | |
| bool | m_updateProgress = true |
| Progress updates won't be called unless this is true. | |
| bool | m_updateBetter = false |
| Update progress only if cost function has improved. | |
| bool | m_progressUpdateDisplay = false |
| Flag whether the Optimizer should set the Update Display flag when reporting progress. | |
| std::string | m_progressText |
| Optional custom description to use for progress reporting. | |
| bool | m_studyOrig = false |
| If true, random study includes original parameters. | |
| Mode | m_mode = OPT |
| Mode of operation (optimization, study or plot) | |
| double | m_range = 1.0 |
| Range for random study or plot. | |
| int | m_steps = 1 |
| Number of steps for random study or plot. | |
| std::vector< double > | m_lowerBounds |
| Lower bounds for bound-constrained optimization. | |
| std::vector< double > | m_upperBounds |
| Upper bounds for bound-constrained optimization. | |
| std::vector< double > | m_scale |
| Parameter scaling (i.e. step sizes) | |
| std::vector< bool > | m_sel |
| Parameter selection for optimization. | |
| std::vector< std::string > | m_paramNames |
| Names of each parameter. | |
| bool | m_first = true |
| Is this the first cost function evaluation. | |
| bool | m_auxPars = false |
| Are auxiliary parameters in use. | |
| std::atomic< bool > | m_aborted {false} |
| Optimizer was aborted. | |
| int | m_run = 0 |
| Current run (for repeated optimization) | |
| int | m_eval = 0 |
| Actual number of cost function evaluations. | |
| double | m_time = 0.0 |
| Execution time of the optimizer. | |
| double | m_firstVal = 0.0 |
| First cost function value. | |
| double | m_bestVal = 0.0 |
| Best cost function value so far. | |
| double | m_doneEst = 0.0 |
| Estimation of completeness. | |
| std::vector< double > | m_lastPars |
| Last parameter vector for assessing completeness. | |
| std::vector< double > | m_firstError |
| First values of optional errors. | |
| std::vector< double > | m_error |
| Current values of optional errors. | |
| double * | m_pars = nullptr |
| The original parameter vector. | |
| std::vector< double > | m_parGradients |
| std::string | m_logFilename |
| Custom log file name or path. | |
| std::ofstream | m_logFile |
| The log file. | |
| float * | m_plotData = nullptr |
| Plot result data. | |
| Protected Attributes inherited from Configurable | |
| std::vector< Param > | m_params |
| List of all registered Parameter and SubProperty instances. | |
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overridevirtual |
Configure this object instance by de-serializing the given Properties.
The default implementation will do so automatically for all registered Parameter and SubProperty instances.
Reimplemented from Optimizer.
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overridevirtual |
Serialize the current object configuration into the given Properties object.
The default implementation will do so automatically for all registered Parameter and SubProperty instances.
Reimplemented from Optimizer.
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inline |
Set initial standard deviations for the parameters by supplying a vector<double> of values.
As a rule of thumb, set it to the distance you expect the optimimum to difer from the initial value. Alternatively, you can use setInitVariance(double var) to set a single value for all dimensions. If the vector is shorter than the number of dimensions, the default variance is used for the dimensions that are not covered by the vector.
| void setSparseMode | ( | bool | sparse = true | ) |
Set the mode of the optimizer to SPARSE.
Supply false as argument to turn SPARSE off. In sparse mode, by default the covariance matrix only updates the diagonal. Additional correlations have to be add expicitly using addSparseCorrelation(int k, int l) The SPARSE mode can be used to optimize large dimensional problems
| void addSparseConnection | ( | int | k, |
| int | l ) |
Add a sparse correlation when using the algorithm in SPARSE mode.
In SPARSE mode, the correlation matrix is only updated for the diagonal and the connections explicitly added using this function.
