public bool Optimize(Vector <double> resultAndInitPos, IFunctionWithDerivative function, double minDerivCompMaxMagn,
Action <int, Func <Vector <double> > > iterationCallback, CancellationToken ct)
{
Contract.Requires(resultAndInitPos.Count == function.DimensionsCount);
Contract.Requires(minDerivCompMaxMagn > 0);
double minStep = minDerivCompMaxMagn / 100;
int[] prevStepSigns = new int[function.DimensionsCount];
var stepSize = new DenseVector(function.DimensionsCount);
var derivative = new DenseVector(function.DimensionsCount);
for (int i = 0; i < stepSize.Count; ++i)
{
stepSize[i] = initialStep;
}
for (int iter = 0; iter < maxIters; ++iter)
{
if (ct.IsCancellationRequested)
{
break;
}
// Compute current derivative.
function.Derivate(derivative, resultAndInitPos);
if (derivative.AbsoluteMaximum() < minDerivCompMaxMagn)
{
return(true);
}
// Update step sizes and step weights.
for (int i = 0; i < prevStepSigns.Length; ++i)
{
int currSign = Math.Sign(derivative[i]);
int sign = currSign * prevStepSigns[i];
if (sign > 0)
{
stepSize[i] = Math.Min(maxStep, stepSize[i] * stepUpMult);
}
else if (sign < 0)
{
stepSize[i] = Math.Max(minStep, stepSize[i] * stepDownMult);
currSign = 0;
}
resultAndInitPos[i] -= currSign * stepSize[i];
prevStepSigns[i] = currSign;
}
if (iterationCallback != null)
{
iterationCallback(iter, resultAndInitPos.Clone);
}
}
return(false);
}
public void TestRandomizeEpsilonIsApplied()
{
int count = 1000;
double epsFactor = 0.2;
double maxAbs = 1.0;
Vector <double> vec = new DenseVector(count);
for (int i = 0; i < count; i++)
{
vec[i] = MathHelper.RandomExceptZero(maxAbs, epsFactor);
}
double min = vec.AbsoluteMinimum();
double max = vec.AbsoluteMaximum();
Assert.IsTrue(min >= epsFactor * maxAbs);
Assert.IsTrue(max <= maxAbs);
}
public bool Optimize(Vector <double> resultAndInitPos, IFunctionWithDerivative function, double minDerivCompMaxMagn,
Action <int, Func <Vector <double> > > iterationCallback, CancellationToken ct)
{
Contract.Requires(resultAndInitPos.Count == function.DimensionsCount);
Contract.Requires(minDerivCompMaxMagn > 0);
var derivative = new DenseVector(function.DimensionsCount);
var prevStep = new DenseVector(function.DimensionsCount);
var position = new DenseVector(function.DimensionsCount);
for (int iter = 0; iter < maxIters; ++iter)
{
if (ct.IsCancellationRequested)
{
break;
}
resultAndInitPos.CopyTo(position);
double momentum = momentumStart + (momentumEnd - momentumStart) * ((double)iter / maxIters);
// Compute derivative take step to point + momentum * prevStep and compute derivative there.
prevStep.Multiply(momentum, prevStep);
prevStep.Add(position, resultAndInitPos);
function.Derivate(derivative, resultAndInitPos);
if (derivative.AbsoluteMaximum() < minDerivCompMaxMagn)
{
return(true);
}
// Scale derivative and subtract from result to take "correction" step.
derivative.Multiply(step, derivative);
resultAndInitPos.Subtract(derivative, resultAndInitPos);
// Conpute prevStep as (result - point).
resultAndInitPos.Subtract(position, prevStep);
if (iterationCallback != null)
{
iterationCallback(iter, resultAndInitPos.Clone);
}
}
return(false);
}
public bool Optimize(Vector <double> resultAndInitPos, IFunctionWithDerivative function, double minDerivCompMaxMagn,
Action <int, Func <Vector <double> > > iterationCallback, CancellationToken ct)
{
Contract.Requires(resultAndInitPos.Count == function.DimensionsCount);
Contract.Requires(minDerivCompMaxMagn > 0);
var derivative = new DenseVector(function.DimensionsCount);
var prevStep = new DenseVector(function.DimensionsCount);
for (int iter = 0; iter < maxIters; ++iter)
{
if (ct.IsCancellationRequested)
{
break;
}
function.Derivate(derivative, resultAndInitPos);
if (derivative.AbsoluteMaximum() < minDerivCompMaxMagn)
{
return(true);
}
derivative.Multiply(step, derivative);
double momentum = momentumStart + (momentumEnd - momentumStart) * ((double)iter / maxIters);
prevStep.Multiply(momentum, prevStep);
prevStep.Add(derivative, prevStep);
resultAndInitPos.Subtract(prevStep, resultAndInitPos);
if (iterationCallback != null)
{
iterationCallback(iter, resultAndInitPos.Clone);
}
}
return(false);
}
public static Tuple <int, int, double> DenseMatrixAbsoluteMaximumPosition(DenseMatrix dm)
{
if (dm == null)
{
return(new Tuple <int, int, double>(0, 0, 0.0d));
}
List <Tuple <int, double> > rowMaxValues = new List <Tuple <int, double> >();
var rowEnum = dm.EnumerateRowsIndexed();
foreach (Tuple <int, Vector <double> > curRow in rowEnum)
{
DenseVector curDV = (DenseVector)curRow.Item2;
rowMaxValues.Add(new Tuple <int, double>(curDV.AbsoluteMaximumIndex(), curDV.AbsoluteMaximum()));
}
double maxValue = rowMaxValues.Max(tpl => tpl.Item2);
int maxValueRow = rowMaxValues.FindIndex(tpl => tpl.Item2 == maxValue);
DenseVector maxRow = (DenseVector)dm.Row(maxValueRow);
return(new Tuple <int, int, double>(maxValueRow, maxRow.AbsoluteMaximumIndex(), maxValue));
}
