public class PowellOptimizer extends AbstractScalarDifferentiableOptimizer
optimize.py
v0.5 of
SciPy).Modifier and Type | Field and Description |
---|---|
static double |
DEFAULT_LS_ABSOLUTE_TOLERANCE
Default absolute tolerance for line search (1.0E-11).
|
static double |
DEFAULT_LS_RELATIVE_TOLERANCE
Default relative tolerance for line search (1.0E-7).
|
checker, DEFAULT_MAX_ITERATIONS, goal, point
Constructor and Description |
---|
PowellOptimizer()
Constructor with default line search tolerances (see the
other constructor ). |
PowellOptimizer(double lsRelativeTolerance)
Constructor with default absolute line search tolerances (see
the
other constructor ). |
PowellOptimizer(double lsRelativeTolerance,
double lsAbsoluteTolerance) |
Modifier and Type | Method and Description |
---|---|
protected RealPointValuePair |
doOptimize()
Perform the bulk of optimization algorithm.
|
computeObjectiveGradient, computeObjectiveValue, getConvergenceChecker, getEvaluations, getGradientEvaluations, getIterations, getMaxEvaluations, getMaxIterations, incrementIterationsCounter, optimize, setConvergenceChecker, setMaxEvaluations, setMaxIterations
public static final double DEFAULT_LS_RELATIVE_TOLERANCE
public static final double DEFAULT_LS_ABSOLUTE_TOLERANCE
public PowellOptimizer()
other constructor
).public PowellOptimizer(double lsRelativeTolerance)
other constructor
).lsRelativeTolerance
- Relative error tolerance for
the line search algorithm (BrentOptimizer
).public PowellOptimizer(double lsRelativeTolerance, double lsAbsoluteTolerance)
lsRelativeTolerance
- Relative error tolerance for
the line search algorithm (BrentOptimizer
).lsAbsoluteTolerance
- Relative error tolerance for
the line search algorithm (BrentOptimizer
).protected RealPointValuePair doOptimize() throws FunctionEvaluationException, OptimizationException
doOptimize
in class AbstractScalarDifferentiableOptimizer
FunctionEvaluationException
- if the objective function throws one during
the searchOptimizationException
- if the algorithm failed to convergeCopyright © 2003–2015. All rights reserved.